diff --git a/.Rbuildignore b/.Rbuildignore
new file mode 100644
index 0000000..6c04d75
--- /dev/null
+++ b/.Rbuildignore
@@ -0,0 +1,32 @@
+\.Rcheck$
+\.Rout$
+\.Rproj$
+\.tar\.gz$
+^GPATH$
+^GRTAGS$
+^GTAGS$
+^LICENSE$
+^Makefile$
+^README\.Rmd$
+^README\.html$
+^README_cache$
+^TAGS$
+^TODO\.org$
+^\#
+^\.Rhistory$
+^\.Rproj\.user$
+^\.\#
+^\.clang_complete$
+^\.clangd$
+^\.git$
+^\.github$
+^\.gitlab-ci.yml$
+^\.travis\.yml$
+^_pkgdown\.yml$
+^appveyor\.yml$
+^docs$
+^misc$
+^revdep$
+^test$
+^working$
+~$
diff --git a/DESCRIPTION b/DESCRIPTION
new file mode 100644
index 0000000..33871e1
--- /dev/null
+++ b/DESCRIPTION
@@ -0,0 +1,28 @@
+Package: ibist
+Title: Data and Functions for Introduction to Biostatistics with R
+Version: 0.1-0
+Authors@R: c(
+ person(given = "Elizabeth", family = "Schifano",
+ role = c("aut"),
+ comment = c(ORCID = "0000-0002-9793-332X")),
+ person(given = "Jun", family = "Yan",
+ email = "jun.yan@uconn.edu",
+ role = c("aut", "cre"),
+ comment = c(ORCID = "0000-0003-4401-7296"))
+ )
+Description: Provides datasets and supporting functions for the book
+ Introduction to Biostatistics with R by Schifano and Yan (2026+),
+ published by Taylor & Francis. The package is intended for teaching
+ introductory biostatistics and for reproducing examples in the text.
+Depends:
+ R (>= 4.4.0)
+VignetteBuilder: knitr
+License: GPL (>= 3)
+URL: https://github.com/statds/ibist-R
+BugReports: https://github.com/statds/ibist-R/issues
+Imports: stats, rlang, ggplot2
+Suggests: knitr, testthat (>= 3.0.0)
+LazyData: true
+RoxygenNote: 7.3.2
+Encoding: UTF-8
+Config/testthat/edition: 3
diff --git a/LICENSE b/LICENSE
deleted file mode 100644
index 0ad25db..0000000
--- a/LICENSE
+++ /dev/null
@@ -1,661 +0,0 @@
- GNU AFFERO GENERAL PUBLIC LICENSE
- Version 3, 19 November 2007
-
- Copyright (C) 2007 Free Software Foundation, Inc.
- Everyone is permitted to copy and distribute verbatim copies
- of this license document, but changing it is not allowed.
-
- Preamble
-
- The GNU Affero General Public License is a free, copyleft license for
-software and other kinds of works, specifically designed to ensure
-cooperation with the community in the case of network server software.
-
- The licenses for most software and other practical works are designed
-to take away your freedom to share and change the works. By contrast,
-our General Public Licenses are intended to guarantee your freedom to
-share and change all versions of a program--to make sure it remains free
-software for all its users.
-
- When we speak of free software, we are referring to freedom, not
-price. Our General Public Licenses are designed to make sure that you
-have the freedom to distribute copies of free software (and charge for
-them if you wish), that you receive source code or can get it if you
-want it, that you can change the software or use pieces of it in new
-free programs, and that you know you can do these things.
-
- Developers that use our General Public Licenses protect your rights
-with two steps: (1) assert copyright on the software, and (2) offer
-you this License which gives you legal permission to copy, distribute
-and/or modify the software.
-
- A secondary benefit of defending all users' freedom is that
-improvements made in alternate versions of the program, if they
-receive widespread use, become available for other developers to
-incorporate. Many developers of free software are heartened and
-encouraged by the resulting cooperation. However, in the case of
-software used on network servers, this result may fail to come about.
-The GNU General Public License permits making a modified version and
-letting the public access it on a server without ever releasing its
-source code to the public.
-
- The GNU Affero General Public License is designed specifically to
-ensure that, in such cases, the modified source code becomes available
-to the community. It requires the operator of a network server to
-provide the source code of the modified version running there to the
-users of that server. Therefore, public use of a modified version, on
-a publicly accessible server, gives the public access to the source
-code of the modified version.
-
- An older license, called the Affero General Public License and
-published by Affero, was designed to accomplish similar goals. This is
-a different license, not a version of the Affero GPL, but Affero has
-released a new version of the Affero GPL which permits relicensing under
-this license.
-
- The precise terms and conditions for copying, distribution and
-modification follow.
-
- TERMS AND CONDITIONS
-
- 0. Definitions.
-
- "This License" refers to version 3 of the GNU Affero General Public License.
-
- "Copyright" also means copyright-like laws that apply to other kinds of
-works, such as semiconductor masks.
-
- "The Program" refers to any copyrightable work licensed under this
-License. Each licensee is addressed as "you". "Licensees" and
-"recipients" may be individuals or organizations.
-
- To "modify" a work means to copy from or adapt all or part of the work
-in a fashion requiring copyright permission, other than the making of an
-exact copy. The resulting work is called a "modified version" of the
-earlier work or a work "based on" the earlier work.
-
- A "covered work" means either the unmodified Program or a work based
-on the Program.
-
- To "propagate" a work means to do anything with it that, without
-permission, would make you directly or secondarily liable for
-infringement under applicable copyright law, except executing it on a
-computer or modifying a private copy. Propagation includes copying,
-distribution (with or without modification), making available to the
-public, and in some countries other activities as well.
-
- To "convey" a work means any kind of propagation that enables other
-parties to make or receive copies. Mere interaction with a user through
-a computer network, with no transfer of a copy, is not conveying.
-
- An interactive user interface displays "Appropriate Legal Notices"
-to the extent that it includes a convenient and prominently visible
-feature that (1) displays an appropriate copyright notice, and (2)
-tells the user that there is no warranty for the work (except to the
-extent that warranties are provided), that licensees may convey the
-work under this License, and how to view a copy of this License. If
-the interface presents a list of user commands or options, such as a
-menu, a prominent item in the list meets this criterion.
-
- 1. Source Code.
-
- The "source code" for a work means the preferred form of the work
-for making modifications to it. "Object code" means any non-source
-form of a work.
-
- A "Standard Interface" means an interface that either is an official
-standard defined by a recognized standards body, or, in the case of
-interfaces specified for a particular programming language, one that
-is widely used among developers working in that language.
-
- The "System Libraries" of an executable work include anything, other
-than the work as a whole, that (a) is included in the normal form of
-packaging a Major Component, but which is not part of that Major
-Component, and (b) serves only to enable use of the work with that
-Major Component, or to implement a Standard Interface for which an
-implementation is available to the public in source code form. A
-"Major Component", in this context, means a major essential component
-(kernel, window system, and so on) of the specific operating system
-(if any) on which the executable work runs, or a compiler used to
-produce the work, or an object code interpreter used to run it.
-
- The "Corresponding Source" for a work in object code form means all
-the source code needed to generate, install, and (for an executable
-work) run the object code and to modify the work, including scripts to
-control those activities. However, it does not include the work's
-System Libraries, or general-purpose tools or generally available free
-programs which are used unmodified in performing those activities but
-which are not part of the work. For example, Corresponding Source
-includes interface definition files associated with source files for
-the work, and the source code for shared libraries and dynamically
-linked subprograms that the work is specifically designed to require,
-such as by intimate data communication or control flow between those
-subprograms and other parts of the work.
-
- The Corresponding Source need not include anything that users
-can regenerate automatically from other parts of the Corresponding
-Source.
-
- The Corresponding Source for a work in source code form is that
-same work.
-
- 2. Basic Permissions.
-
- All rights granted under this License are granted for the term of
-copyright on the Program, and are irrevocable provided the stated
-conditions are met. This License explicitly affirms your unlimited
-permission to run the unmodified Program. The output from running a
-covered work is covered by this License only if the output, given its
-content, constitutes a covered work. This License acknowledges your
-rights of fair use or other equivalent, as provided by copyright law.
-
- You may make, run and propagate covered works that you do not
-convey, without conditions so long as your license otherwise remains
-in force. You may convey covered works to others for the sole purpose
-of having them make modifications exclusively for you, or provide you
-with facilities for running those works, provided that you comply with
-the terms of this License in conveying all material for which you do
-not control copyright. Those thus making or running the covered works
-for you must do so exclusively on your behalf, under your direction
-and control, on terms that prohibit them from making any copies of
-your copyrighted material outside their relationship with you.
-
- Conveying under any other circumstances is permitted solely under
-the conditions stated below. Sublicensing is not allowed; section 10
-makes it unnecessary.
-
- 3. Protecting Users' Legal Rights From Anti-Circumvention Law.
-
- No covered work shall be deemed part of an effective technological
-measure under any applicable law fulfilling obligations under article
-11 of the WIPO copyright treaty adopted on 20 December 1996, or
-similar laws prohibiting or restricting circumvention of such
-measures.
-
- When you convey a covered work, you waive any legal power to forbid
-circumvention of technological measures to the extent such circumvention
-is effected by exercising rights under this License with respect to
-the covered work, and you disclaim any intention to limit operation or
-modification of the work as a means of enforcing, against the work's
-users, your or third parties' legal rights to forbid circumvention of
-technological measures.
-
- 4. Conveying Verbatim Copies.
-
- You may convey verbatim copies of the Program's source code as you
-receive it, in any medium, provided that you conspicuously and
-appropriately publish on each copy an appropriate copyright notice;
-keep intact all notices stating that this License and any
-non-permissive terms added in accord with section 7 apply to the code;
-keep intact all notices of the absence of any warranty; and give all
-recipients a copy of this License along with the Program.
-
- You may charge any price or no price for each copy that you convey,
-and you may offer support or warranty protection for a fee.
-
- 5. Conveying Modified Source Versions.
-
- You may convey a work based on the Program, or the modifications to
-produce it from the Program, in the form of source code under the
-terms of section 4, provided that you also meet all of these conditions:
-
- a) The work must carry prominent notices stating that you modified
- it, and giving a relevant date.
-
- b) The work must carry prominent notices stating that it is
- released under this License and any conditions added under section
- 7. This requirement modifies the requirement in section 4 to
- "keep intact all notices".
-
- c) You must license the entire work, as a whole, under this
- License to anyone who comes into possession of a copy. This
- License will therefore apply, along with any applicable section 7
- additional terms, to the whole of the work, and all its parts,
- regardless of how they are packaged. This License gives no
- permission to license the work in any other way, but it does not
- invalidate such permission if you have separately received it.
-
- d) If the work has interactive user interfaces, each must display
- Appropriate Legal Notices; however, if the Program has interactive
- interfaces that do not display Appropriate Legal Notices, your
- work need not make them do so.
-
- A compilation of a covered work with other separate and independent
-works, which are not by their nature extensions of the covered work,
-and which are not combined with it such as to form a larger program,
-in or on a volume of a storage or distribution medium, is called an
-"aggregate" if the compilation and its resulting copyright are not
-used to limit the access or legal rights of the compilation's users
-beyond what the individual works permit. Inclusion of a covered work
-in an aggregate does not cause this License to apply to the other
-parts of the aggregate.
-
- 6. Conveying Non-Source Forms.
-
- You may convey a covered work in object code form under the terms
-of sections 4 and 5, provided that you also convey the
-machine-readable Corresponding Source under the terms of this License,
-in one of these ways:
-
- a) Convey the object code in, or embodied in, a physical product
- (including a physical distribution medium), accompanied by the
- Corresponding Source fixed on a durable physical medium
- customarily used for software interchange.
-
- b) Convey the object code in, or embodied in, a physical product
- (including a physical distribution medium), accompanied by a
- written offer, valid for at least three years and valid for as
- long as you offer spare parts or customer support for that product
- model, to give anyone who possesses the object code either (1) a
- copy of the Corresponding Source for all the software in the
- product that is covered by this License, on a durable physical
- medium customarily used for software interchange, for a price no
- more than your reasonable cost of physically performing this
- conveying of source, or (2) access to copy the
- Corresponding Source from a network server at no charge.
-
- c) Convey individual copies of the object code with a copy of the
- written offer to provide the Corresponding Source. This
- alternative is allowed only occasionally and noncommercially, and
- only if you received the object code with such an offer, in accord
- with subsection 6b.
-
- d) Convey the object code by offering access from a designated
- place (gratis or for a charge), and offer equivalent access to the
- Corresponding Source in the same way through the same place at no
- further charge. You need not require recipients to copy the
- Corresponding Source along with the object code. If the place to
- copy the object code is a network server, the Corresponding Source
- may be on a different server (operated by you or a third party)
- that supports equivalent copying facilities, provided you maintain
- clear directions next to the object code saying where to find the
- Corresponding Source. Regardless of what server hosts the
- Corresponding Source, you remain obligated to ensure that it is
- available for as long as needed to satisfy these requirements.
-
- e) Convey the object code using peer-to-peer transmission, provided
- you inform other peers where the object code and Corresponding
- Source of the work are being offered to the general public at no
- charge under subsection 6d.
-
- A separable portion of the object code, whose source code is excluded
-from the Corresponding Source as a System Library, need not be
-included in conveying the object code work.
-
- A "User Product" is either (1) a "consumer product", which means any
-tangible personal property which is normally used for personal, family,
-or household purposes, or (2) anything designed or sold for incorporation
-into a dwelling. In determining whether a product is a consumer product,
-doubtful cases shall be resolved in favor of coverage. For a particular
-product received by a particular user, "normally used" refers to a
-typical or common use of that class of product, regardless of the status
-of the particular user or of the way in which the particular user
-actually uses, or expects or is expected to use, the product. A product
-is a consumer product regardless of whether the product has substantial
-commercial, industrial or non-consumer uses, unless such uses represent
-the only significant mode of use of the product.
-
- "Installation Information" for a User Product means any methods,
-procedures, authorization keys, or other information required to install
-and execute modified versions of a covered work in that User Product from
-a modified version of its Corresponding Source. The information must
-suffice to ensure that the continued functioning of the modified object
-code is in no case prevented or interfered with solely because
-modification has been made.
-
- If you convey an object code work under this section in, or with, or
-specifically for use in, a User Product, and the conveying occurs as
-part of a transaction in which the right of possession and use of the
-User Product is transferred to the recipient in perpetuity or for a
-fixed term (regardless of how the transaction is characterized), the
-Corresponding Source conveyed under this section must be accompanied
-by the Installation Information. But this requirement does not apply
-if neither you nor any third party retains the ability to install
-modified object code on the User Product (for example, the work has
-been installed in ROM).
-
- The requirement to provide Installation Information does not include a
-requirement to continue to provide support service, warranty, or updates
-for a work that has been modified or installed by the recipient, or for
-the User Product in which it has been modified or installed. Access to a
-network may be denied when the modification itself materially and
-adversely affects the operation of the network or violates the rules and
-protocols for communication across the network.
-
- Corresponding Source conveyed, and Installation Information provided,
-in accord with this section must be in a format that is publicly
-documented (and with an implementation available to the public in
-source code form), and must require no special password or key for
-unpacking, reading or copying.
-
- 7. Additional Terms.
-
- "Additional permissions" are terms that supplement the terms of this
-License by making exceptions from one or more of its conditions.
-Additional permissions that are applicable to the entire Program shall
-be treated as though they were included in this License, to the extent
-that they are valid under applicable law. If additional permissions
-apply only to part of the Program, that part may be used separately
-under those permissions, but the entire Program remains governed by
-this License without regard to the additional permissions.
-
- When you convey a copy of a covered work, you may at your option
-remove any additional permissions from that copy, or from any part of
-it. (Additional permissions may be written to require their own
-removal in certain cases when you modify the work.) You may place
-additional permissions on material, added by you to a covered work,
-for which you have or can give appropriate copyright permission.
-
- Notwithstanding any other provision of this License, for material you
-add to a covered work, you may (if authorized by the copyright holders of
-that material) supplement the terms of this License with terms:
-
- a) Disclaiming warranty or limiting liability differently from the
- terms of sections 15 and 16 of this License; or
-
- b) Requiring preservation of specified reasonable legal notices or
- author attributions in that material or in the Appropriate Legal
- Notices displayed by works containing it; or
-
- c) Prohibiting misrepresentation of the origin of that material, or
- requiring that modified versions of such material be marked in
- reasonable ways as different from the original version; or
-
- d) Limiting the use for publicity purposes of names of licensors or
- authors of the material; or
-
- e) Declining to grant rights under trademark law for use of some
- trade names, trademarks, or service marks; or
-
- f) Requiring indemnification of licensors and authors of that
- material by anyone who conveys the material (or modified versions of
- it) with contractual assumptions of liability to the recipient, for
- any liability that these contractual assumptions directly impose on
- those licensors and authors.
-
- All other non-permissive additional terms are considered "further
-restrictions" within the meaning of section 10. If the Program as you
-received it, or any part of it, contains a notice stating that it is
-governed by this License along with a term that is a further
-restriction, you may remove that term. If a license document contains
-a further restriction but permits relicensing or conveying under this
-License, you may add to a covered work material governed by the terms
-of that license document, provided that the further restriction does
-not survive such relicensing or conveying.
-
- If you add terms to a covered work in accord with this section, you
-must place, in the relevant source files, a statement of the
-additional terms that apply to those files, or a notice indicating
-where to find the applicable terms.
-
- Additional terms, permissive or non-permissive, may be stated in the
-form of a separately written license, or stated as exceptions;
-the above requirements apply either way.
-
- 8. Termination.
-
- You may not propagate or modify a covered work except as expressly
-provided under this License. Any attempt otherwise to propagate or
-modify it is void, and will automatically terminate your rights under
-this License (including any patent licenses granted under the third
-paragraph of section 11).
-
- However, if you cease all violation of this License, then your
-license from a particular copyright holder is reinstated (a)
-provisionally, unless and until the copyright holder explicitly and
-finally terminates your license, and (b) permanently, if the copyright
-holder fails to notify you of the violation by some reasonable means
-prior to 60 days after the cessation.
-
- Moreover, your license from a particular copyright holder is
-reinstated permanently if the copyright holder notifies you of the
-violation by some reasonable means, this is the first time you have
-received notice of violation of this License (for any work) from that
-copyright holder, and you cure the violation prior to 30 days after
-your receipt of the notice.
-
- Termination of your rights under this section does not terminate the
-licenses of parties who have received copies or rights from you under
-this License. If your rights have been terminated and not permanently
-reinstated, you do not qualify to receive new licenses for the same
-material under section 10.
-
- 9. Acceptance Not Required for Having Copies.
-
- You are not required to accept this License in order to receive or
-run a copy of the Program. Ancillary propagation of a covered work
-occurring solely as a consequence of using peer-to-peer transmission
-to receive a copy likewise does not require acceptance. However,
-nothing other than this License grants you permission to propagate or
-modify any covered work. These actions infringe copyright if you do
-not accept this License. Therefore, by modifying or propagating a
-covered work, you indicate your acceptance of this License to do so.
-
- 10. Automatic Licensing of Downstream Recipients.
-
- Each time you convey a covered work, the recipient automatically
-receives a license from the original licensors, to run, modify and
-propagate that work, subject to this License. You are not responsible
-for enforcing compliance by third parties with this License.
-
- An "entity transaction" is a transaction transferring control of an
-organization, or substantially all assets of one, or subdividing an
-organization, or merging organizations. If propagation of a covered
-work results from an entity transaction, each party to that
-transaction who receives a copy of the work also receives whatever
-licenses to the work the party's predecessor in interest had or could
-give under the previous paragraph, plus a right to possession of the
-Corresponding Source of the work from the predecessor in interest, if
-the predecessor has it or can get it with reasonable efforts.
-
- You may not impose any further restrictions on the exercise of the
-rights granted or affirmed under this License. For example, you may
-not impose a license fee, royalty, or other charge for exercise of
-rights granted under this License, and you may not initiate litigation
-(including a cross-claim or counterclaim in a lawsuit) alleging that
-any patent claim is infringed by making, using, selling, offering for
-sale, or importing the Program or any portion of it.
-
- 11. Patents.
-
- A "contributor" is a copyright holder who authorizes use under this
-License of the Program or a work on which the Program is based. The
-work thus licensed is called the contributor's "contributor version".
-
- A contributor's "essential patent claims" are all patent claims
-owned or controlled by the contributor, whether already acquired or
-hereafter acquired, that would be infringed by some manner, permitted
-by this License, of making, using, or selling its contributor version,
-but do not include claims that would be infringed only as a
-consequence of further modification of the contributor version. For
-purposes of this definition, "control" includes the right to grant
-patent sublicenses in a manner consistent with the requirements of
-this License.
-
- Each contributor grants you a non-exclusive, worldwide, royalty-free
-patent license under the contributor's essential patent claims, to
-make, use, sell, offer for sale, import and otherwise run, modify and
-propagate the contents of its contributor version.
-
- In the following three paragraphs, a "patent license" is any express
-agreement or commitment, however denominated, not to enforce a patent
-(such as an express permission to practice a patent or covenant not to
-sue for patent infringement). To "grant" such a patent license to a
-party means to make such an agreement or commitment not to enforce a
-patent against the party.
-
- If you convey a covered work, knowingly relying on a patent license,
-and the Corresponding Source of the work is not available for anyone
-to copy, free of charge and under the terms of this License, through a
-publicly available network server or other readily accessible means,
-then you must either (1) cause the Corresponding Source to be so
-available, or (2) arrange to deprive yourself of the benefit of the
-patent license for this particular work, or (3) arrange, in a manner
-consistent with the requirements of this License, to extend the patent
-license to downstream recipients. "Knowingly relying" means you have
-actual knowledge that, but for the patent license, your conveying the
-covered work in a country, or your recipient's use of the covered work
-in a country, would infringe one or more identifiable patents in that
-country that you have reason to believe are valid.
-
- If, pursuant to or in connection with a single transaction or
-arrangement, you convey, or propagate by procuring conveyance of, a
-covered work, and grant a patent license to some of the parties
-receiving the covered work authorizing them to use, propagate, modify
-or convey a specific copy of the covered work, then the patent license
-you grant is automatically extended to all recipients of the covered
-work and works based on it.
-
- A patent license is "discriminatory" if it does not include within
-the scope of its coverage, prohibits the exercise of, or is
-conditioned on the non-exercise of one or more of the rights that are
-specifically granted under this License. You may not convey a covered
-work if you are a party to an arrangement with a third party that is
-in the business of distributing software, under which you make payment
-to the third party based on the extent of your activity of conveying
-the work, and under which the third party grants, to any of the
-parties who would receive the covered work from you, a discriminatory
-patent license (a) in connection with copies of the covered work
-conveyed by you (or copies made from those copies), or (b) primarily
-for and in connection with specific products or compilations that
-contain the covered work, unless you entered into that arrangement,
-or that patent license was granted, prior to 28 March 2007.
-
- Nothing in this License shall be construed as excluding or limiting
-any implied license or other defenses to infringement that may
-otherwise be available to you under applicable patent law.
-
- 12. No Surrender of Others' Freedom.
-
- If conditions are imposed on you (whether by court order, agreement or
-otherwise) that contradict the conditions of this License, they do not
-excuse you from the conditions of this License. If you cannot convey a
-covered work so as to satisfy simultaneously your obligations under this
-License and any other pertinent obligations, then as a consequence you may
-not convey it at all. For example, if you agree to terms that obligate you
-to collect a royalty for further conveying from those to whom you convey
-the Program, the only way you could satisfy both those terms and this
-License would be to refrain entirely from conveying the Program.
-
- 13. Remote Network Interaction; Use with the GNU General Public License.
-
- Notwithstanding any other provision of this License, if you modify the
-Program, your modified version must prominently offer all users
-interacting with it remotely through a computer network (if your version
-supports such interaction) an opportunity to receive the Corresponding
-Source of your version by providing access to the Corresponding Source
-from a network server at no charge, through some standard or customary
-means of facilitating copying of software. This Corresponding Source
-shall include the Corresponding Source for any work covered by version 3
-of the GNU General Public License that is incorporated pursuant to the
-following paragraph.
-
- Notwithstanding any other provision of this License, you have
-permission to link or combine any covered work with a work licensed
-under version 3 of the GNU General Public License into a single
-combined work, and to convey the resulting work. The terms of this
-License will continue to apply to the part which is the covered work,
-but the work with which it is combined will remain governed by version
-3 of the GNU General Public License.
-
- 14. Revised Versions of this License.
-
- The Free Software Foundation may publish revised and/or new versions of
-the GNU Affero General Public License from time to time. Such new versions
-will be similar in spirit to the present version, but may differ in detail to
-address new problems or concerns.
-
- Each version is given a distinguishing version number. If the
-Program specifies that a certain numbered version of the GNU Affero General
-Public License "or any later version" applies to it, you have the
-option of following the terms and conditions either of that numbered
-version or of any later version published by the Free Software
-Foundation. If the Program does not specify a version number of the
-GNU Affero General Public License, you may choose any version ever published
-by the Free Software Foundation.
-
- If the Program specifies that a proxy can decide which future
-versions of the GNU Affero General Public License can be used, that proxy's
-public statement of acceptance of a version permanently authorizes you
-to choose that version for the Program.
-
- Later license versions may give you additional or different
-permissions. However, no additional obligations are imposed on any
-author or copyright holder as a result of your choosing to follow a
-later version.
-
- 15. Disclaimer of Warranty.
-
- THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
-APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
-HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
-OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
-THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
-PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
-IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
-ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
-
- 16. Limitation of Liability.
-
- IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
-WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
-THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
-GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
-USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
-DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
-PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
-EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
-SUCH DAMAGES.
-
- 17. Interpretation of Sections 15 and 16.
-
- If the disclaimer of warranty and limitation of liability provided
-above cannot be given local legal effect according to their terms,
-reviewing courts shall apply local law that most closely approximates
-an absolute waiver of all civil liability in connection with the
-Program, unless a warranty or assumption of liability accompanies a
-copy of the Program in return for a fee.
-
- END OF TERMS AND CONDITIONS
-
- How to Apply These Terms to Your New Programs
-
- If you develop a new program, and you want it to be of the greatest
-possible use to the public, the best way to achieve this is to make it
-free software which everyone can redistribute and change under these terms.
-
- To do so, attach the following notices to the program. It is safest
-to attach them to the start of each source file to most effectively
-state the exclusion of warranty; and each file should have at least
-the "copyright" line and a pointer to where the full notice is found.
-
-
- Copyright (C)
-
- This program is free software: you can redistribute it and/or modify
- it under the terms of the GNU Affero General Public License as published
- by the Free Software Foundation, either version 3 of the License, or
- (at your option) any later version.
-
- This program is distributed in the hope that it will be useful,
- but WITHOUT ANY WARRANTY; without even the implied warranty of
- MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- GNU Affero General Public License for more details.
-
- You should have received a copy of the GNU Affero General Public License
- along with this program. If not, see .
-
-Also add information on how to contact you by electronic and paper mail.
-
- If your software can interact with users remotely through a computer
-network, you should also make sure that it provides a way for users to
-get its source. For example, if your program is a web application, its
-interface could display a "Source" link that leads users to an archive
-of the code. There are many ways you could offer source, and different
-solutions will be better for different programs; see section 13 for the
-specific requirements.
-
- You should also get your employer (if you work as a programmer) or school,
-if any, to sign a "copyright disclaimer" for the program, if necessary.
-For more information on this, and how to apply and follow the GNU AGPL, see
-.
diff --git a/Makefile b/Makefile
new file mode 100644
index 0000000..7ed9975
--- /dev/null
+++ b/Makefile
@@ -0,0 +1,74 @@
+objects := $(wildcard R/*.R) DESCRIPTION
+version := $(shell grep -E "^Version:" DESCRIPTION | awk '{print $$NF}')
+pkg := $(shell grep -E "^Package:" DESCRIPTION | awk '{print $$NF}')
+tar := $(pkg)_$(version).tar.gz
+tinytest := $(wildcard inst/tinytest/*.R)
+checkLog := $(pkg).Rcheck/00check.log
+rmd := $(wildcard vignettes/*.Rmd)
+vignettes := $(patsubst %.Rmd,%.html,$(rmd))
+
+
+.PHONY: check
+check: $(checkLog)
+
+.PHONY: build
+build: $(tar)
+
+.PHONY: install
+install:
+ R CMD build .
+ R CMD INSTALL $(tar)
+
+.PHONY: preview
+preview: $(vignettes)
+
+.PHONY: pkgdown
+pkgdown:
+ Rscript -e "library(methods); pkgdown::build_site();"
+
+.PHONY: deploy-pkgdown
+deploy-pkgdown:
+ @bash misc/deploy_docs.sh
+
+.PHONY: check-rcpp
+check-rcpp: $(tar)
+ R CMD INSTALL $(tar)
+ Rscript inst/run_rcpp_test.R > check-rcpp.Rout &
+
+.PHONY: check-revdep
+check-revdep: $(tar)
+ @mkdir -p revdep
+ @rm -rf revdep/{*.Rcheck,*.tar.gz}
+ @cp $(tar) revdep
+ nohup R CMD BATCH --no-save --no-restore misc/revdep_check.R &
+
+$(tar): $(objects)
+ @Rscript -e "library(methods);" \
+ -e "devtools::document();";
+ @$(MAKE) update-timestamp
+ R CMD build .
+
+$(checkLog): $(tar) $(tinytest)
+ R CMD check --as-cran $(tar)
+
+vignettes/%.html: vignettes/%.Rmd
+ Rscript -e "library(methods); rmarkdown::render('$?')"
+
+.PHONY: readme
+readme: README.md
+README.md: README.Rmd
+ @Rscript -e "rmarkdown::render('$<')"
+
+## update copyright year
+.PHONY: update-timestamp
+update-timestamp:
+ @bash misc/update_timestamp.sh
+
+.PHONY: tags
+tags:
+ Rscript -e "utils::rtags(path = 'R', ofile = 'TAGS')"
+
+.PHONY: clean
+clean:
+ @$(RM) -r *~ */*~ *.Rhistroy *.tar.gz src/*.so src/*.o \
+ *.Rcheck/ *.Rout .\#* *_cache
diff --git a/NAMESPACE b/NAMESPACE
new file mode 100644
index 0000000..f7d3888
--- /dev/null
+++ b/NAMESPACE
@@ -0,0 +1,22 @@
+# Generated by roxygen2: do not edit by hand
+
+export(demo_clt)
+export(power.p1s.test)
+export(rate.test)
+importFrom(ggplot2,aes)
+importFrom(ggplot2,after_stat)
+importFrom(ggplot2,facet_wrap)
+importFrom(ggplot2,geom_histogram)
+importFrom(ggplot2,geom_line)
+importFrom(ggplot2,ggplot)
+importFrom(ggplot2,labs)
+importFrom(ggplot2,theme_minimal)
+importFrom(rlang,.data)
+importFrom(stats,dbinom)
+importFrom(stats,density)
+importFrom(stats,dnorm)
+importFrom(stats,pbinom)
+importFrom(stats,pnorm)
+importFrom(stats,qbinom)
+importFrom(stats,qnorm)
+importFrom(stats,uniroot)
diff --git a/R/data-nrs.R b/R/data-nrs.R
new file mode 100644
index 0000000..a17d783
--- /dev/null
+++ b/R/data-nrs.R
@@ -0,0 +1,43 @@
+#' Non-restorative sleep and physical activity (Japan cohort study)
+#'
+#' A large observational dataset from a cohort study conducted in Japan
+#' to examine the association between non-restorative sleep (NRS) and
+#' physical activity, gender, and age. The data are used to illustrate
+#' logistic regression modeling for a binary outcome in a large-sample
+#' setting.
+#'
+#' @format
+#' A data frame with 90,122 observations on the following variables:
+#' \describe{
+#' \item{id}{Subject identifier.}
+#' \item{Gender}{Gender of the subject (integer-coded).}
+#' \item{Age_2013}{Age in years in 2013.}
+#' \item{EX_2013}{Indicator of regular exercise in 2013
+#' (integer-coded).}
+#' \item{PA_2013}{Physical activity measure in 2013
+#' (integer-coded).}
+#' \item{NRS_2013}{Indicator of non-restorative sleep in 2013
+#' (1 = presence, 0 = absence).}
+#' \item{AgeGroup_2013}{Categorical age group in 2013
+#' (integer-coded).}
+#' \item{EXPA_classification}{Combined classification of exercise and
+#' physical activity status (integer-coded).}
+#' }
+#'
+#' @details
+#' Non-restorative sleep (NRS) is defined as a subjective feeling of lack
+#' of refreshment on awakening and reflects qualitative aspects of sleep.
+#' Hidaka et al. (2019) analyzed these data using logistic regression to
+#' assess whether the probability of NRS is associated with physical
+#' activity, gender, and age in a large cohort of adult subjects in
+#' Japan. Within this package, the dataset is provided for methodological
+#' illustration of binary regression models rather than for substantive
+#' epidemiological inference.
+#'
+#' All variables are stored as integer codes. Missing values are
+#' represented as \code{NA}.
+#'
+#' @source
+#' Hidaka et al. (2019).
+#'
+"nrs"
diff --git a/R/demo_clt.R b/R/demo_clt.R
new file mode 100644
index 0000000..9fe0f64
--- /dev/null
+++ b/R/demo_clt.R
@@ -0,0 +1,120 @@
+#' Demonstrate the Central Limit Theorem
+#'
+#' The \code{demo_clt()} function generates plots to illustrate the
+#' Central Limit Theorem (CLT) using a specified random number generator.
+#' The function displays standardized sampling distributions for
+#' different sample sizes and overlays the standard normal density.
+#'
+#' @param rng A random number generator function taking the sample size
+#' as its first argument (e.g., \code{runif}, \code{rnorm},
+#' \code{rgamma}).
+#' @param n A numeric vector of sample sizes (e.g., \code{c(5, 10, 20,
+#' 40)}).
+#' @param nrep The number of repetitions for generating sample means
+#' (default is 10000).
+#' @param ... Additional arguments passed to the random number generator
+#' (e.g., \code{shape} and \code{rate} for \code{rgamma}).
+#' @param pmean The population mean of the distribution. If \code{NULL},
+#' it is estimated from a large Monte Carlo sample.
+#' @param psd The population standard deviation of the distribution.
+#' If \code{NULL}, it is estimated from a large Monte Carlo sample.
+#'
+#' @return A \code{ggplot2} object showing the standardized sampling
+#' distributions for different sample sizes, compared against the
+#' standard normal curve.
+#'
+#' @examples
+#' set.seed(123)
+#' demo_clt(runif, n = c(5, 10, 20, 40), min = 0, max = 1)
+#'
+#' demo_clt(rgamma, n = c(5, 10, 20, 40), shape = 2, rate = 1,
+#' pmean = 2, psd = sqrt(2)
+#' )
+#'
+#' @importFrom rlang .data
+#' @importFrom ggplot2 ggplot geom_histogram geom_line aes
+#' @importFrom ggplot2 facet_wrap labs theme_minimal after_stat
+#' @export
+demo_clt <- function(
+ rng,
+ n,
+ nrep = 10000,
+ ...,
+ pmean = NULL,
+ psd = NULL
+) {
+ ## ---- basic validation ----
+ if (!is.function(rng)) {
+ stop("The argument 'rng' must be a function.", call. = FALSE)
+ }
+
+ if (!is.numeric(n) || any(n <= 0)) {
+ stop(
+ "The argument 'n' must be a numeric vector of positive values.",
+ call. = FALSE
+ )
+ }
+
+ if (!is.numeric(nrep) || length(nrep) != 1L || nrep <= 0) {
+ stop(
+ "The argument 'nrep' must be a positive integer.",
+ call. = FALSE
+ )
+ }
+
+ ## ---- estimate pmean and psd if needed ----
+ if (is.null(pmean) || is.null(psd)) {
+ sample_data <- rng(100000, ...)
+ if (is.null(pmean)) pmean <- base::mean(sample_data)
+ if (is.null(psd)) psd <- stats::sd(sample_data)
+ }
+
+ ## ---- generate standardized sample means ----
+ results <- vector("list", length(n))
+ names(results) <- as.character(n)
+
+ for (size in n) {
+ rng_local <- function() rng(size, ...)
+ sample_means <- replicate(nrep, base::mean(rng_local()))
+
+ results[[as.character(size)]] <- data.frame(
+ StdMean = (sample_means - pmean) / (psd / sqrt(size)),
+ SampleSize = size
+ )
+ }
+
+ data <- do.call(rbind, results)
+
+ ## ---- standard normal reference ----
+ x_vals <- seq(-4, 4, length.out = 200)
+ normal_data <- data.frame(
+ x = x_vals,
+ y = stats::dnorm(x_vals)
+ )
+
+ ## ---- plot ----
+ ggplot2::ggplot(
+ data,
+ ggplot2::aes(x = .data$StdMean)
+ ) +
+ ggplot2::geom_histogram(
+ ggplot2::aes(y = ggplot2::after_stat(density)),
+ bins = 30,
+ color = "black",
+ fill = "skyblue"
+ ) +
+ ggplot2::geom_line(
+ data = normal_data,
+ ggplot2::aes(x = .data$x, y = .data$y),
+ color = "red",
+ linetype = "dashed",
+ linewidth = 0.8
+ ) +
+ ggplot2::facet_wrap(~ SampleSize) +
+ ggplot2::labs(
+ title = "Demonstrating the Central Limit Theorem",
+ x = "Standardized sample mean",
+ y = "Density"
+ ) +
+ ggplot2::theme_minimal()
+}
diff --git a/R/power.p1s.test.R b/R/power.p1s.test.R
new file mode 100644
index 0000000..d1f1c0a
--- /dev/null
+++ b/R/power.p1s.test.R
@@ -0,0 +1,307 @@
+#' One-sample proportion power and sample size calculation
+#'
+#' Computes power, sample size, or detectable effect size for a
+#' one-sample binomial test. The interface mirrors
+#' \code{stats::power.prop.test()}, but for the one-sample setting.
+#'
+#' Power can be computed using a normal approximation or exact binomial
+#' methods. When \code{exact = TRUE}, the exact test is determined by
+#' \code{exact.method}.
+#'
+#' Exactly one of \code{n}, \code{p0}, \code{p1}, \code{power}, or
+#' \code{sig.level} must be \code{NULL}; the missing quantity is solved
+#' numerically.
+#'
+#' @param n Sample size for the single group.
+#' @param p0 Null hypothesis proportion.
+#' @param p1 Alternative hypothesis proportion.
+#' @param power Desired power.
+#' @param sig.level Significance level.
+#' @param alternative Character string specifying the alternative
+#' hypothesis; one of \code{"two.sided"}, \code{"less"}, or
+#' \code{"greater"}.
+#' @param cc Logical; if \code{TRUE}, apply continuity correction in the
+#' normal approximation.
+#' @param exact Logical; if \code{TRUE}, use an exact binomial method.
+#' @param exact.method Method used for exact binomial power calculation.
+#' \code{"quantile"} uses fixed binomial rejection regions for stable
+#' power and sample-size inversion; \code{"midp"} applies the mid-p
+#' adjustment; \code{"cp"} inverts Clopper--Pearson acceptance regions
+#' to guarantee size not exceeding \code{sig.level}.
+#' @param tol Numerical tolerance used in root finding.
+#' @param max_n Maximum allowable sample size when solving for \code{n}.
+#'
+#' @return An object of class \code{"power.htest"} containing the
+#' computed quantity and test specifications.
+#'
+#' @examples
+#' ## Normal approximation (default)
+#' power.p1s.test(n = 50, p0 = 0.1, p1 = 0.25)
+#'
+#' ## Exact binomial power (quantile-based, default exact method)
+#' power.p1s.test(n = 50, p0 = 0.1, p1 = 0.25, exact = TRUE)
+#'
+#' ## Exact mid-p power
+#' power.p1s.test(
+#' n = 50, p0 = 0.1, p1 = 0.25,
+#' exact = TRUE, exact.method = "midp"
+#' )
+#'
+#' ## Exact Clopper--Pearson power (guaranteed size control)
+#' power.p1s.test(
+#' n = 50, p0 = 0.1, p1 = 0.25,
+#' exact = TRUE, exact.method = "cp"
+#' )
+#'
+#' @importFrom stats dbinom pbinom qbinom
+#' @importFrom stats dnorm pnorm qnorm
+#' @importFrom stats uniroot density
+#
+#' @export
+power.p1s.test <- function(
+ n = NULL,
+ p0 = NULL,
+ p1 = NULL,
+ power = NULL,
+ sig.level = 0.05,
+ alternative = c("two.sided", "less", "greater"),
+ cc = FALSE,
+ exact = FALSE,
+ exact.method = c("quantile", "midp", "cp"),
+ tol = .Machine$double.eps^0.5,
+ max_n = 1e7
+) {
+ alternative <- match.arg(alternative)
+ exact.method <- match.arg(exact.method)
+
+ ## ---- argument geometry ----
+ is_null <- c(is.null(n), is.null(p0), is.null(p1),
+ is.null(power), is.null(sig.level))
+ if (sum(is_null) != 1L)
+ stop("Exactly one of 'n', 'p0', 'p1', 'power', 'sig.level' must be NULL",
+ call. = FALSE)
+
+ ## ---- basic validation ----
+ if (!is.null(n)) {
+ if (!is.finite(n) || n <= 0)
+ stop("'n' must be positive", call. = FALSE)
+ n <- as.integer(ceiling(n))
+ }
+ if (!is.null(p0) && !(p0 > 0 && p0 < 1))
+ stop("'p0' must be in (0,1)", call. = FALSE)
+ if (!is.null(p1) && !(p1 > 0 && p1 < 1))
+ stop("'p1' must be in (0,1)", call. = FALSE)
+ if (!is.null(sig.level) && !(sig.level > 0 && sig.level < 1))
+ stop("'sig.level' must be in (0,1)", call. = FALSE)
+ if (!is.null(power) && !(power > 0 && power < 1))
+ stop("'power' must be in (0,1)", call. = FALSE)
+
+ if (!exact && exact.method != "quantile") {
+ warning(
+ "'exact.method' ignored when exact = FALSE",
+ call. = FALSE
+ )
+ }
+
+ midp = exact.method == "midp"
+
+ ## ---- exact quantile rejection region cache ----
+ rr_cache <- new.env(parent = emptyenv())
+
+ get_rr <- function(n, p0, sig.level) {
+ key <- paste(n, p0, sig.level, alternative, sep = "|")
+ if (exists(key, envir = rr_cache, inherits = FALSE))
+ return(get(key, envir = rr_cache, inherits = FALSE))
+
+ if (alternative == "greater") {
+ rr <- list(type = "greater",
+ k = qbinom(1 - sig.level, n, p0) + 1L)
+ } else if (alternative == "less") {
+ rr <- list(type = "less",
+ k = qbinom(sig.level, n, p0) - 1L)
+ } else {
+ rr <- list(
+ type = "two.sided",
+ k_lo = qbinom(sig.level / 2, n, p0) - 1L,
+ k_hi = qbinom(1 - sig.level / 2, n, p0) + 1L
+ )
+ }
+
+ assign(key, rr, envir = rr_cache)
+ rr
+ }
+
+ ## ---- power bodies ----
+
+ approx_power_body <- quote({
+ se0 <- sqrt(p0 * (1 - p0) / n)
+ se1 <- sqrt(p1 * (1 - p1) / n)
+ delta <- if (cc) 0.5 / n else 0
+
+ if (alternative == "greater") {
+ z <- qnorm(1 - sig.level)
+ 1 - pnorm((p0 + z * se0 + delta - p1) / se1)
+ } else if (alternative == "less") {
+ z <- qnorm(1 - sig.level)
+ pnorm((p0 - z * se0 - delta - p1) / se1)
+ } else {
+ z <- qnorm(1 - sig.level / 2)
+ pnorm((p0 - z * se0 - delta - p1) / se1) +
+ 1 - pnorm((p0 + z * se0 + delta - p1) / se1)
+ }
+ })
+
+ exact_quantile_power_body <- quote({
+ rr <- get_rr(n, p0, sig.level)
+
+ if (rr$type == "greater") {
+ k <- rr$k
+ if (midp)
+ pbinom(k - 1, n, p1, lower.tail = FALSE) +
+ 0.5 * dbinom(k, n, p1)
+ else
+ pbinom(k - 1, n, p1, lower.tail = FALSE)
+ } else if (rr$type == "less") {
+ k <- rr$k
+ if (midp)
+ pbinom(k - 1, n, p1) + 0.5 * dbinom(k, n, p1)
+ else
+ pbinom(k, n, p1)
+ } else {
+ k_lo <- rr$k_lo
+ k_hi <- rr$k_hi
+ if (midp) {
+ pbinom(k_lo - 1, n, p1) +
+ 0.5 * dbinom(k_lo, n, p1) +
+ pbinom(k_hi - 1, n, p1, lower.tail = FALSE) +
+ 0.5 * dbinom(k_hi, n, p1)
+ } else {
+ pbinom(k_lo, n, p1) +
+ pbinom(k_hi - 1, n, p1, lower.tail = FALSE)
+ }
+ }
+ })
+
+ cp_power_body <- quote({
+ x <- 0:n
+ reject <- if (alternative == "greater") {
+ pbinom(x - 1, n, p0, lower.tail = FALSE) <= sig.level
+ } else if (alternative == "less") {
+ pbinom(x, n, p0) <= sig.level
+ } else {
+ 2 * pmin(
+ pbinom(x, n, p0),
+ pbinom(x - 1, n, p0, lower.tail = FALSE)
+ ) <= sig.level
+ }
+ sum(dbinom(x[reject], n, p1))
+ })
+
+ ## ---- dispatch ----
+ if (!exact) {
+ power_body <- approx_power_body
+ midp <- NA
+ } else if (exact.method == "cp") {
+ power_body <- cp_power_body
+ midp <- NA
+ } else {
+ power_body <- exact_quantile_power_body
+ }
+
+ ## ---- solve for missing parameter ----
+ if (is.null(power)) {
+ power <- eval(power_body)
+ }
+
+ if (is.null(n)) {
+ if (!exact) {
+ n <- uniroot(function(n) eval(power_body) - power,
+ c(1, max_n), tol = tol,
+ extendInt = "upX")$root
+ } else {
+ power_at_n <- function(nn) {
+ n <- as.integer(nn)
+ eval(power_body)
+ }
+
+ alpha_at_n <- function(nn) {
+ n <- as.integer(nn)
+ p1 <- p0
+ eval(power_body)
+ }
+
+ if (exact.method == "cp") {
+ feasible <- function(nn) {
+ (power_at_n(nn) >= power)
+ }
+
+ } else {
+ ## quantile / mid-p: enforce size <= nominal (optionally also add
+ ## a tol.alpha rule if you want parity across exact methods).
+ feasible <- function(nn) {
+ (alpha_at_n(nn) <= sig.level) &&
+ (power_at_n(nn) >= power)
+ }
+ }
+
+ ## ---- exponential bracketing + integer bisection ----
+ n_lo <- 1L
+ if (feasible(n_lo)) {
+ n <- n_lo
+ } else {
+ n_hi <- 2L
+ while (!feasible(n_hi)) {
+ n_lo <- n_hi
+ n_hi <- n_hi * 2L
+ if (n_hi > max_n)
+ stop("Required n exceeds 'max_n'", call. = FALSE)
+ }
+ while (n_hi - n_lo > 1L) {
+ n_mid <- (n_lo + n_hi) %/% 2L
+ if (feasible(n_mid)) n_hi <- n_mid else n_lo <- n_mid
+ }
+ n <- n_hi
+ }
+ power <- power_at_n(n)
+ }
+ }
+
+
+ if (is.null(p1)) {
+ p1 <- uniroot(function(pp) eval(power_body) - power,
+ c(tol, 1 - tol), tol = tol)$root
+ }
+
+ if (is.null(p0)) {
+ p0 <- uniroot(function(pp) eval(power_body) - power,
+ c(tol, 1 - tol), tol = tol)$root
+ }
+
+ if (is.null(sig.level)) {
+ sig.level <- uniroot(function(a) eval(power_body) - power,
+ c(tol, 1 - tol), tol = tol)$root
+ }
+
+ ## ---- return object ----
+ method <- if (!exact)
+ "One-sample proportion power calculation (normal approximation)"
+ else if (exact.method == "cp")
+ "One-sample proportion power calculation (exact Clopper--Pearson)"
+ else if (exact.method == "midp")
+ "One-sample proportion power calculation (exact binomial, mid-p)"
+ else
+ "One-sample proportion power calculation (exact binomial)"
+
+ structure(
+ list(
+ n = n,
+ p0 = p0,
+ p1 = p1,
+ sig.level = sig.level,
+ power = power,
+ alternative = alternative,
+ method = method
+ ),
+ class = "power.htest"
+ )
+}
diff --git a/R/rate_test.R b/R/rate_test.R
new file mode 100644
index 0000000..61c6f81
--- /dev/null
+++ b/R/rate_test.R
@@ -0,0 +1,218 @@
+#' Test of Poisson Rates Using Normal Approximation
+#'
+#' Performs a large-sample (normal) test for one or two Poisson rates with known
+#' exposures. The test is carried out on the observed count scale and then
+#' translated to rates for reporting.
+#'
+#' @param x a vector of event counts. A single value specifies a one-sample
+#' test; a vector of length two specifies a two-sample comparison.
+#' @param T a vector of exposures corresponding to \code{x} (e.g., person-time).
+#' Must have the same length as \code{x}.
+#' @param r a positive number specifying the null rate per unit exposure,
+#' \eqn{\lambda_0}, for a one-sample test. Ignored for two-sample tests.
+#' @param alternative a character string specifying the alternative hypothesis,
+#' one of \code{"two.sided"}, \code{"less"}, or \code{"greater"}.
+#' @param conf.level confidence level for the confidence interval.
+#' @param correct logical; if \code{TRUE}, applies a continuity correction on
+#' the count scale. For one-sample tests, a \eqn{\pm 0.5} correction is applied
+#' to \eqn{x} in the direction determined by \code{alternative}. For
+#' \code{"two.sided"}, the correction uses the sign of \eqn{x-\mu_0}.
+#'
+#' @details
+#' One-sample test:
+#' Assume \eqn{X \sim \mathrm{Pois}(\mu)} with \eqn{\mu = \lambda T}. The null
+#' hypothesis is \eqn{H_0:\lambda=\lambda_0}, where \eqn{\lambda_0=r}. Let
+#' \eqn{\mu_0=\lambda_0 T}. The normal approximation gives
+#' \deqn{Z = \frac{(x - c) - \mu_0}{\sqrt{\mu_0}} \approx N(0,1),}
+#' where \eqn{c} is 0 if \code{correct=FALSE} and is a continuity correction on
+#' the count scale if \code{correct=TRUE}. Two-sided p-values use
+#' \eqn{2\{1-\Phi(|Z|)\}}.
+#'
+#' #' Two-sample test:
+#' Assume independent \eqn{X_1 \sim \mathrm{Pois}(\lambda_1 T_1)} and
+#' \eqn{X_2 \sim \mathrm{Pois}(\lambda_2 T_2)} with known exposures
+#' \eqn{T_1} and \eqn{T_2}. The null hypothesis is
+#' \eqn{H_0:\lambda_1=\lambda_2}.
+#'
+#' For hypothesis testing, the function uses the exact conditional
+#' representation under \eqn{H_0}:
+#' \deqn{
+#' X_1 \mid (X_1+X_2=n)
+#' \sim
+#' \mathrm{Binom}\!\left(n,\; \frac{T_1}{T_1+T_2}\right),
+#' }
+#' and applies the same large-sample normal approximation as
+#' \code{\link[stats]{prop.test}} (with optional Yates continuity correction)
+#' to obtain the test statistic and p-value.
+#'
+#' For estimation and confidence intervals, the inference target is the
+#' difference between the two rates,
+#' \eqn{\Delta = \lambda_1 - \lambda_2}.
+#' The point estimate is
+#' \eqn{\hat\Delta = X_1/T_1 - X_2/T_2}, and the confidence interval is
+#' constructed using a normal approximation with estimated standard error
+#' \deqn{
+#' \sqrt{X_1/T_1^2 + X_2/T_2^2}.
+#' }
+#' The continuity correction affects the hypothesis test but not the
+#' confidence interval for \eqn{\Delta}.
+#'
+#' Confidence intervals:
+#' For one-sample tests, the confidence interval is for \eqn{\lambda} and is
+#' obtained by inverting the same normal approximation on the count scale for
+#' \eqn{\mu=\lambda T}, then dividing by \eqn{T}.
+#' For two-sample tests, the confidence interval is for the difference in rates
+#' \eqn{\lambda_1-\lambda_2}, analogous to the difference in proportions in
+#' \code{\link[stats]{prop.test}}.
+#'
+#' @return
+#' An object of class \code{"htest"} containing:
+#' \item{statistic}{the standardized normal statistic \code{z}.}
+#' \item{parameter}{degrees of freedom (\code{df = 1}).}
+#' \item{p.value}{the p-value.}
+#' \item{conf.int}{a confidence interval for the difference between the two
+#' rates, \eqn{\lambda_1-\lambda_2}, for two-sample tests.}
+#' \item{estimate}{estimated rate (one-sample) or estimated rates (two-sample).}
+#' \item{null.value}{the null rate (one-sample) or the null rate difference
+#' \eqn{\lambda_1-\lambda_2=0} (two-sample).}
+#' \item{alternative}{the alternative hypothesis.}
+#' \item{method}{a character string describing the test.}
+#' \item{data.name}{a character string describing the data.}
+#'
+#' @seealso
+#' \code{\link[stats]{prop.test}}, \code{\link[stats]{poisson.test}}
+#'
+#' @examples
+#' ## One-sample test: compare observed rate to a reference unit rate
+#' rate.test(x = 411, T = 25800, r = 0.0119)
+#' rate.test(x = 411, T = 25800, r = 0.0119, correct = FALSE)
+#'
+#' ## Two-sample test: compare two Poisson rates
+#' rate.test(x = c(12, 5), T = c(100, 80))
+#' rate.test(x = c(12, 5), T = c(100, 80), correct = FALSE)
+#'
+#' ## One-sided alternative
+#' rate.test(x = 411, T = 25800, r = 0.0119, alternative = "greater")
+#'
+#' @export
+rate.test <- function(x, T, r = NULL,
+ alternative = c("two.sided", "less", "greater"),
+ conf.level = 0.95,
+ correct = TRUE)
+{
+ alternative <- match.arg(alternative)
+
+ if (length(x) != length(T)) stop("'x' and 'T' must have the same length")
+ if (!length(x) %in% c(1L, 2L)) stop("'x' must have length 1 or 2")
+ if (any(!is.finite(x)) || any(!is.finite(T))) stop("'x' and 'T' must be finite")
+ if (any(x < 0) || any(abs(x - round(x)) > 0)) stop("'x' must be nonnegative integers")
+ if (any(T <= 0)) stop("'T' must be positive")
+ if (!is.numeric(conf.level) || length(conf.level) != 1L ||
+ conf.level <= 0 || conf.level >= 1) {
+ stop("'conf.level' must be a single number in (0, 1)")
+ }
+
+ zcrit <- qnorm(1 - (1 - conf.level) / 2)
+
+ if (length(x) == 1L) {
+ ## --- One-sample: H0: lambda = r (unit rate)
+ if (is.null(r) || length(r) != 1L || !is.finite(r) || r <= 0) {
+ stop("a single positive null unit rate 'r' must be specified")
+ }
+
+ mu0 <- r * T
+
+ ## CC on count scale
+ cc <- 0
+ if (isTRUE(correct)) {
+ cc <- switch(alternative,
+ "greater" = 0.5,
+ "less" = -0.5,
+ "two.sided" = if (x == mu0) 0 else 0.5 * sign(x - mu0)
+ )
+ }
+
+ ## Standardize observed count against null mean (score-style)
+ z <- (x - cc - mu0) / sqrt(mu0)
+
+ p.value <- switch(alternative,
+ "two.sided" = 2 * pnorm(-abs(z)),
+ "less" = pnorm(z),
+ "greater" = pnorm(z, lower.tail = FALSE)
+ )
+
+ ## CI for lambda by inverting |(x-c)-mu|/sqrt(mu) <= zcrit, then /T
+ x_adj <- x - cc
+ disc <- zcrit^2 + 4 * x_adj
+ mu_lo <- 0.5 * (zcrit^2 + 2 * x_adj - zcrit * sqrt(disc))
+ mu_hi <- 0.5 * (zcrit^2 + 2 * x_adj + zcrit * sqrt(disc))
+ mu_lo <- max(0, mu_lo)
+ conf.int <- c(mu_lo, mu_hi) / T
+
+ estimate <- c(rate = x / T)
+ null.value <- c(rate = r)
+
+ ## Ingredients (shared names)
+ statistic <- c(z = as.numeric(z))
+ parameter <- c(df = 1)
+ method <- "Normal approximation test for a Poisson rate"
+ data.name <- paste0("x = ", x, ", T = ", T)
+
+ } else {
+
+ ## --- Two-sample: H0: lambda1 = lambda2
+ x1 <- x[1]; x2 <- x[2]
+ T1 <- T[1]; T2 <- T[2]
+
+ if (x1 + x2 == 0) {
+ stop("at least one event is required for the 2-sample test")
+ }
+
+ ## Conditional binomial test under H0 via prop.test()
+ n <- x1 + x2
+ p0 <- T1 / (T1 + T2)
+
+ pt <- stats::prop.test(x = x1, n = n,p = p0, alternative = alternative,
+ conf.level = conf.level, correct = correct)
+
+ ## Estimation target: difference in rates
+ rate1 <- x1 / T1
+ rate2 <- x2 / T2
+ diff_hat <- rate1 - rate2
+
+ se_diff <- sqrt(x1 / T1^2 + x2 / T2^2)
+ conf.int <- diff_hat + c(-1, 1) * zcrit * se_diff
+
+ estimate <- c("rate 1" = rate1, "rate 2" = rate2)
+ null.value <- c("rate difference" = 0)
+
+ ## Ingredients (shared names)
+ statistic <- pt$statistic
+ parameter <- pt$parameter
+ p.value <- pt$p.value
+ method <- paste(
+ "2-sample test for equality of Poisson rates",
+ "(conditional binomial normal approximation);",
+ "CI for rate difference by normal approximation"
+ )
+ data.name <- paste0(
+ "x = c(", x1, ", ", x2, "), ",
+ "T = c(", T1, ", ", T2, ")"
+ )
+ }
+
+ ## --- Shared return block (single place)
+ rval <- list(
+ statistic = statistic,
+ parameter = parameter,
+ p.value = as.numeric(p.value),
+ conf.int = structure(conf.int, conf.level = conf.level),
+ estimate = estimate,
+ null.value = null.value,
+ alternative = alternative,
+ method = method,
+ data.name = data.name
+ )
+ class(rval) <- "htest"
+ rval
+}
diff --git a/README.md b/README.md
index 26cc5b3..0c2b914 100644
--- a/README.md
+++ b/README.md
@@ -1 +1,26 @@
-# ibist
\ No newline at end of file
+# R Package **ibist**
+
+The R package **ibist** is a companion to the book
+"Introduction to Biostatistical Analysis of Proportions and Rates"
+by Elizabeth D. Schifano and Jun Yan
+
+## Features
+
+The package **splines2** provides functions, datasets, and demos
+used in the book.
+
+## Development
+
+The latest version of the package is under development at
+[GitHub](https://github.com/wenjie2wang/splines2). If it is able to pass
+the automated package checks, one may install it by
+
+``` r
+if (! require(remotes)) install.packages("remotes")
+remotes::install_github("statds/ibist-R", upgrade = "never")
+```
+
+## License
+
+[GNU General Public License](https://www.gnu.org/licenses/) (≥ 3)
+
diff --git a/data-raw/nrs.R b/data-raw/nrs.R
new file mode 100644
index 0000000..efa0f00
--- /dev/null
+++ b/data-raw/nrs.R
@@ -0,0 +1,5 @@
+## data-raw/nrs.R
+
+nrs <- read.csv("data-raw/nrs.csv", header = TRUE)
+
+usethis::use_data(nrs, overwrite = TRUE)
diff --git a/data/nrs.rda b/data/nrs.rda
new file mode 100644
index 0000000..019dc9d
Binary files /dev/null and b/data/nrs.rda differ
diff --git a/inst/bib/refs.bib b/inst/bib/refs.bib
new file mode 100644
index 0000000..5b7901a
--- /dev/null
+++ b/inst/bib/refs.bib
@@ -0,0 +1,17 @@
+
+
+@article{wang2021shape,
+ author = {Wang, Wenjie and Yan, Jun},
+ title = {Shape-Restricted Regression Splines with {R} Package
+ {splines2}},
+ journal = {Journal of Data Science},
+ volume = 19,
+ number = 3,
+ year = 2021,
+ pages = {498--517},
+ doi = {10.6339/21-JDS1020},
+ issn = {1680-743X},
+ publisher = {School of Statistics, Renmin University of China},
+}
+
+
diff --git a/man/demo_clt.Rd b/man/demo_clt.Rd
new file mode 100644
index 0000000..8ec2dfa
--- /dev/null
+++ b/man/demo_clt.Rd
@@ -0,0 +1,48 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/demo_clt.R
+\name{demo_clt}
+\alias{demo_clt}
+\title{Demonstrate the Central Limit Theorem}
+\usage{
+demo_clt(rng, n, nrep = 10000, ..., pmean = NULL, psd = NULL)
+}
+\arguments{
+\item{rng}{A random number generator function taking the sample size
+as its first argument (e.g., \code{runif}, \code{rnorm},
+\code{rgamma}).}
+
+\item{n}{A numeric vector of sample sizes (e.g., \code{c(5, 10, 20,
+40)}).}
+
+\item{nrep}{The number of repetitions for generating sample means
+(default is 10000).}
+
+\item{...}{Additional arguments passed to the random number generator
+(e.g., \code{shape} and \code{rate} for \code{rgamma}).}
+
+\item{pmean}{The population mean of the distribution. If \code{NULL},
+it is estimated from a large Monte Carlo sample.}
+
+\item{psd}{The population standard deviation of the distribution.
+If \code{NULL}, it is estimated from a large Monte Carlo sample.}
+}
+\value{
+A \code{ggplot2} object showing the standardized sampling
+ distributions for different sample sizes, compared against the
+ standard normal curve.
+}
+\description{
+The \code{demo_clt()} function generates plots to illustrate the
+Central Limit Theorem (CLT) using a specified random number generator.
+The function displays standardized sampling distributions for
+different sample sizes and overlays the standard normal density.
+}
+\examples{
+set.seed(123)
+demo_clt(runif, n = c(5, 10, 20, 40), min = 0, max = 1)
+
+demo_clt(rgamma, n = c(5, 10, 20, 40), shape = 2, rate = 1,
+ pmean = 2, psd = sqrt(2)
+)
+
+}
diff --git a/man/nrs.Rd b/man/nrs.Rd
new file mode 100644
index 0000000..575a0d6
--- /dev/null
+++ b/man/nrs.Rd
@@ -0,0 +1,51 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/data-nrs.R
+\docType{data}
+\name{nrs}
+\alias{nrs}
+\title{Non-restorative sleep and physical activity (Japan cohort study)}
+\format{
+A data frame with 90,122 observations on the following variables:
+\describe{
+ \item{id}{Subject identifier.}
+ \item{Gender}{Gender of the subject (integer-coded).}
+ \item{Age_2013}{Age in years in 2013.}
+ \item{EX_2013}{Indicator of regular exercise in 2013
+ (integer-coded).}
+ \item{PA_2013}{Physical activity measure in 2013
+ (integer-coded).}
+ \item{NRS_2013}{Indicator of non-restorative sleep in 2013
+ (1 = presence, 0 = absence).}
+ \item{AgeGroup_2013}{Categorical age group in 2013
+ (integer-coded).}
+ \item{EXPA_classification}{Combined classification of exercise and
+ physical activity status (integer-coded).}
+}
+}
+\source{
+Hidaka et al. (2019).
+}
+\usage{
+nrs
+}
+\description{
+A large observational dataset from a cohort study conducted in Japan
+to examine the association between non-restorative sleep (NRS) and
+physical activity, gender, and age. The data are used to illustrate
+logistic regression modeling for a binary outcome in a large-sample
+setting.
+}
+\details{
+Non-restorative sleep (NRS) is defined as a subjective feeling of lack
+of refreshment on awakening and reflects qualitative aspects of sleep.
+Hidaka et al. (2019) analyzed these data using logistic regression to
+assess whether the probability of NRS is associated with physical
+activity, gender, and age in a large cohort of adult subjects in
+Japan. Within this package, the dataset is provided for methodological
+illustration of binary regression models rather than for substantive
+epidemiological inference.
+
+All variables are stored as integer codes. Missing values are
+represented as \code{NA}.
+}
+\keyword{datasets}
diff --git a/man/power.p1s.test.Rd b/man/power.p1s.test.Rd
new file mode 100644
index 0000000..7e032c7
--- /dev/null
+++ b/man/power.p1s.test.Rd
@@ -0,0 +1,88 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/power.p1s.test.R
+\name{power.p1s.test}
+\alias{power.p1s.test}
+\title{One-sample proportion power and sample size calculation}
+\usage{
+power.p1s.test(
+ n = NULL,
+ p0 = NULL,
+ p1 = NULL,
+ power = NULL,
+ sig.level = 0.05,
+ alternative = c("two.sided", "less", "greater"),
+ cc = FALSE,
+ exact = FALSE,
+ exact.method = c("quantile", "midp", "cp"),
+ tol = .Machine$double.eps^0.5,
+ max_n = 1e+07
+)
+}
+\arguments{
+\item{n}{Sample size for the single group.}
+
+\item{p0}{Null hypothesis proportion.}
+
+\item{p1}{Alternative hypothesis proportion.}
+
+\item{power}{Desired power.}
+
+\item{sig.level}{Significance level.}
+
+\item{alternative}{Character string specifying the alternative
+hypothesis; one of \code{"two.sided"}, \code{"less"}, or
+\code{"greater"}.}
+
+\item{cc}{Logical; if \code{TRUE}, apply continuity correction in the
+normal approximation.}
+
+\item{exact}{Logical; if \code{TRUE}, use an exact binomial method.}
+
+\item{exact.method}{Method used for exact binomial power calculation.
+\code{"quantile"} uses fixed binomial rejection regions for stable
+power and sample-size inversion; \code{"midp"} applies the mid-p
+adjustment; \code{"cp"} inverts Clopper--Pearson acceptance regions
+to guarantee size not exceeding \code{sig.level}.}
+
+\item{tol}{Numerical tolerance used in root finding.}
+
+\item{max_n}{Maximum allowable sample size when solving for \code{n}.}
+}
+\value{
+An object of class \code{"power.htest"} containing the
+ computed quantity and test specifications.
+}
+\description{
+Computes power, sample size, or detectable effect size for a
+one-sample binomial test. The interface mirrors
+\code{stats::power.prop.test()}, but for the one-sample setting.
+}
+\details{
+Power can be computed using a normal approximation or exact binomial
+methods. When \code{exact = TRUE}, the exact test is determined by
+\code{exact.method}.
+
+Exactly one of \code{n}, \code{p0}, \code{p1}, \code{power}, or
+\code{sig.level} must be \code{NULL}; the missing quantity is solved
+numerically.
+}
+\examples{
+## Normal approximation (default)
+power.p1s.test(n = 50, p0 = 0.1, p1 = 0.25)
+
+## Exact binomial power (quantile-based, default exact method)
+power.p1s.test(n = 50, p0 = 0.1, p1 = 0.25, exact = TRUE)
+
+## Exact mid-p power
+power.p1s.test(
+ n = 50, p0 = 0.1, p1 = 0.25,
+ exact = TRUE, exact.method = "midp"
+)
+
+## Exact Clopper--Pearson power (guaranteed size control)
+power.p1s.test(
+ n = 50, p0 = 0.1, p1 = 0.25,
+ exact = TRUE, exact.method = "cp"
+)
+
+}
diff --git a/man/rate.test.Rd b/man/rate.test.Rd
new file mode 100644
index 0000000..bcb58c3
--- /dev/null
+++ b/man/rate.test.Rd
@@ -0,0 +1,117 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/rate_test.R
+\name{rate.test}
+\alias{rate.test}
+\title{Test of Poisson Rates Using Normal Approximation}
+\usage{
+rate.test(
+ x,
+ T,
+ r = NULL,
+ alternative = c("two.sided", "less", "greater"),
+ conf.level = 0.95,
+ correct = TRUE
+)
+}
+\arguments{
+\item{x}{a vector of event counts. A single value specifies a one-sample
+test; a vector of length two specifies a two-sample comparison.}
+
+\item{T}{a vector of exposures corresponding to \code{x} (e.g., person-time).
+Must have the same length as \code{x}.}
+
+\item{r}{a positive number specifying the null rate per unit exposure,
+\eqn{\lambda_0}, for a one-sample test. Ignored for two-sample tests.}
+
+\item{alternative}{a character string specifying the alternative hypothesis,
+one of \code{"two.sided"}, \code{"less"}, or \code{"greater"}.}
+
+\item{conf.level}{confidence level for the confidence interval.}
+
+\item{correct}{logical; if \code{TRUE}, applies a continuity correction on
+the count scale. For one-sample tests, a \eqn{\pm 0.5} correction is applied
+to \eqn{x} in the direction determined by \code{alternative}. For
+\code{"two.sided"}, the correction uses the sign of \eqn{x-\mu_0}.}
+}
+\value{
+An object of class \code{"htest"} containing:
+\item{statistic}{the standardized normal statistic \code{z}.}
+\item{parameter}{degrees of freedom (\code{df = 1}).}
+\item{p.value}{the p-value.}
+\item{conf.int}{a confidence interval for the difference between the two
+ rates, \eqn{\lambda_1-\lambda_2}, for two-sample tests.}
+\item{estimate}{estimated rate (one-sample) or estimated rates (two-sample).}
+\item{null.value}{the null rate (one-sample) or the null rate difference
+ \eqn{\lambda_1-\lambda_2=0} (two-sample).}
+\item{alternative}{the alternative hypothesis.}
+\item{method}{a character string describing the test.}
+\item{data.name}{a character string describing the data.}
+}
+\description{
+Performs a large-sample (normal) test for one or two Poisson rates with known
+exposures. The test is carried out on the observed count scale and then
+translated to rates for reporting.
+}
+\details{
+One-sample test:
+Assume \eqn{X \sim \mathrm{Pois}(\mu)} with \eqn{\mu = \lambda T}. The null
+hypothesis is \eqn{H_0:\lambda=\lambda_0}, where \eqn{\lambda_0=r}. Let
+\eqn{\mu_0=\lambda_0 T}. The normal approximation gives
+\deqn{Z = \frac{(x - c) - \mu_0}{\sqrt{\mu_0}} \approx N(0,1),}
+where \eqn{c} is 0 if \code{correct=FALSE} and is a continuity correction on
+the count scale if \code{correct=TRUE}. Two-sided p-values use
+\eqn{2\{1-\Phi(|Z|)\}}.
+
+#' Two-sample test:
+Assume independent \eqn{X_1 \sim \mathrm{Pois}(\lambda_1 T_1)} and
+\eqn{X_2 \sim \mathrm{Pois}(\lambda_2 T_2)} with known exposures
+\eqn{T_1} and \eqn{T_2}. The null hypothesis is
+\eqn{H_0:\lambda_1=\lambda_2}.
+
+For hypothesis testing, the function uses the exact conditional
+representation under \eqn{H_0}:
+\deqn{
+X_1 \mid (X_1+X_2=n)
+\sim
+\mathrm{Binom}\!\left(n,\; \frac{T_1}{T_1+T_2}\right),
+}
+and applies the same large-sample normal approximation as
+\code{\link[stats]{prop.test}} (with optional Yates continuity correction)
+to obtain the test statistic and p-value.
+
+For estimation and confidence intervals, the inference target is the
+difference between the two rates,
+\eqn{\Delta = \lambda_1 - \lambda_2}.
+The point estimate is
+\eqn{\hat\Delta = X_1/T_1 - X_2/T_2}, and the confidence interval is
+constructed using a normal approximation with estimated standard error
+\deqn{
+\sqrt{X_1/T_1^2 + X_2/T_2^2}.
+}
+The continuity correction affects the hypothesis test but not the
+confidence interval for \eqn{\Delta}.
+
+Confidence intervals:
+For one-sample tests, the confidence interval is for \eqn{\lambda} and is
+obtained by inverting the same normal approximation on the count scale for
+\eqn{\mu=\lambda T}, then dividing by \eqn{T}.
+For two-sample tests, the confidence interval is for the difference in rates
+\eqn{\lambda_1-\lambda_2}, analogous to the difference in proportions in
+\code{\link[stats]{prop.test}}.
+}
+\examples{
+## One-sample test: compare observed rate to a reference unit rate
+rate.test(x = 411, T = 25800, r = 0.0119)
+rate.test(x = 411, T = 25800, r = 0.0119, correct = FALSE)
+
+## Two-sample test: compare two Poisson rates
+rate.test(x = c(12, 5), T = c(100, 80))
+rate.test(x = c(12, 5), T = c(100, 80), correct = FALSE)
+
+## One-sided alternative
+rate.test(x = 411, T = 25800, r = 0.0119, alternative = "greater")
+
+}
+\seealso{
+\code{\link[stats]{prop.test}}, \code{\link[stats]{poisson.test}}
+}
diff --git a/misc/copyright.R b/misc/copyright.R
new file mode 100644
index 0000000..2aca1be
--- /dev/null
+++ b/misc/copyright.R
@@ -0,0 +1,17 @@
+##
+## R package ibist by Elizabeth D. Schifano and Jun Yan
+## Copyright (C) 2024-2025
+##
+## This file is part of the R package ibist.
+##
+## The R package ibist is free software: You can redistribute it and/or
+## modify it under the terms of the GNU General Public License as published by
+## the Free Software Foundation, either version 3 of the License, or any later
+## version (at your option). See the GNU General Public License at
+## for details.
+##
+## The R package ibist is distributed in the hope that it will be useful,
+## but WITHOUT ANY WARRANTY without even the implied warranty of
+## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
+##
+
diff --git a/misc/deploy_docs.sh b/misc/deploy_docs.sh
new file mode 100755
index 0000000..b5732e9
--- /dev/null
+++ b/misc/deploy_docs.sh
@@ -0,0 +1,29 @@
+#!/bin/bash
+
+set -e
+
+## run locally
+PKG=$(grep "Package" DESCRIPTION | awk '{print $NF}')
+BUILD_DIR=$(pwd)
+DOCS_REPO=$HOME/git/wwenjie.org
+TARGET_DIR=$DOCS_REPO/static/$PKG
+GIT_COMMIT=$(git rev-parse --short HEAD)
+
+## update docs by pkgdown
+make pkgdown
+
+# go to the repository for wwenjie.org
+cd $DOCS_REPO
+git checkout -f
+git checkout main
+git pull gitlab main
+mkdir -p $TARGET_DIR
+cp -r $BUILD_DIR/docs/* $TARGET_DIR
+git add static/$PKG/
+if [ -n "$(git diff --cached --exit-code)" ]
+then
+ git commit -m "deploy pkgdown for $PKG $GIT_COMMIT"
+ git push gitlab main
+else
+ printf "The docs was not updated.\n"
+fi
diff --git a/misc/revdep_check.R b/misc/revdep_check.R
new file mode 100644
index 0000000..6495008
--- /dev/null
+++ b/misc/revdep_check.R
@@ -0,0 +1,5 @@
+revdep_dir <- "revdep"
+res <- tools::check_packages_in_dir(revdep_dir,
+ clean = FALSE,
+ reverse = list(recursively = FALSE))
+summary(res)
diff --git a/misc/update_timestamp.sh b/misc/update_timestamp.sh
new file mode 100755
index 0000000..3003f1e
--- /dev/null
+++ b/misc/update_timestamp.sh
@@ -0,0 +1,67 @@
+#!/bin/bash
+
+# Note: this script is should be sourced from the project root directory
+
+set -e
+
+if [ "$(uname)" != "Linux" ]; then
+ printf "Remeber to update date and version number.\n"
+else
+ printf "Updating date, version, and copyright year.\n"
+
+ # define some variables
+ yr=$(date +%Y)
+ dt=$(date +%Y-%m-%d)
+ cprt_R=misc/copyright.R
+ cprt_cpp=misc/copyright.cpp
+ citation=inst/CITATION
+ version=$(grep "Version" DESCRIPTION | awk '{print $NF}')
+
+ # update copyright year in the template headers
+ regexp1="s/Copyright \(C\) 2016-[0-9]+/Copyright \(C\) 2016-$yr/"
+ sed -i -E "$regexp1" $cprt_R
+ sed "s_#_/_g" $cprt_R > $cprt_cpp
+
+ # update copyright year in all R scripts
+ for Rfile in R/*.R
+ do
+ if ! grep -q 'Copyright (C)' $Rfile;
+ then
+ if [ $Rfile != "R/RcppExports.R" ];
+ then
+ cat $cprt_R $Rfile > .tmp
+ mv .tmp $Rfile
+ fi
+ fi
+ sed -i -E "$regexp1" $Rfile
+ done
+
+ # update copyright year in all C++ scripts
+ for cppfile in src/*.cpp inst/include/*.h inst/include/*/*.h
+ do
+ if ! grep -q 'Copyright (C)' $cppfile;
+ then
+ if [ $cppfile != "src/RcppExports.cpp" ];
+ then
+ cat $cprt_cpp $cppfile > .tmp
+ mv .tmp $cppfile
+ fi
+ fi
+ sed -i -E "$regexp1" $cppfile
+ done
+ rm $cprt_cpp
+
+ # update date in DESCRIPTION
+ # regexp2="s/Date: [0-9]{4}-[0-9]{1,2}-[0-9]{1,2}/Date: $dt/"
+ # sed -i -E "$regexp2" DESCRIPTION
+
+ # update version and year in citation
+ regexp3="s/version ([0-9]+\.*)+/version $version/"
+ sed -i -E "$regexp3" $citation
+ # restrict the search and only update the year of package
+ regexp4="/splines2-package/,/^\)$/ s/20[0-9]{2}/$yr/"
+ sed -i -E "$regexp4" $citation
+
+ # done
+ printf "All updated.\n"
+fi
diff --git a/vignettes/clt.Rmd b/vignettes/clt.Rmd
new file mode 100644
index 0000000..820de8d
--- /dev/null
+++ b/vignettes/clt.Rmd
@@ -0,0 +1,98 @@
+mean---
+title: "Demonstrating the Central Limit Theorem"
+author: "Companion Package for Biostatistical Analysis of Proportions and Rates"
+date: "`r Sys.Date()`"
+output: rmarkdown::html_vignette
+vignette: >
+ %\VignetteIndexEntry{Central Limit Theorem Demonstration}
+ %\VignetteEngine{knitr::rmarkdown}
+ %\VignetteEncoding{UTF-8}
+---
+
+# Introduction
+
+In this vignette, we demonstrate the Central Limit Theorem (CLT)
+using the `cltdemo()` function. The CLT states that, regardless
+of the original population distribution, the distribution of the
+sample mean approaches a normal distribution as the sample size
+increases.
+
+Here, we use the Gamma distribution with varying skewness, which
+is controlled by the `shape` parameter:
+
+- **Shape = 0.5**: Highly skewed distribution
+- **Shape = 1**: Exponential distribution (moderately skewed)
+- **Shape = 2**: Less skewed distribution
+
+We explore the behavior of the sample mean for different sample
+sizes (`n = 5, 10, 20, 40`) to illustrate the convergence towards
+the normal distribution.
+
+# Load Required Packages
+
+```{r setup, include = FALSE}
+set.seed(123)
+library("ibist")
+```
+
+# Gamma Distribution with Shape = 0.5
+
+The Gamma distribution with `shape = 0.5` is highly skewed. We
+expect to see the sample mean distribution becoming more normal
+as the sample size increases.
+
+```{r gamma-shape-0.5}
+demo_clt(rgamma, n = c(5, 10, 20, 40), nrep = 10000,
+ shape = 0.5, rate = 1, pmean = 0.5, psd = sqrt(0.5))
+```
+
+# Gamma Distribution with Shape = 1
+
+The Gamma distribution with `shape = 1` is equivalent to the
+Exponential distribution. This example has moderate skewness,
+and we observe the effect of increasing the sample size.
+
+```{r gamma-shape-1}
+demo_clt(rgamma, n = c(5, 10, 20, 40), nrep = 10000,
+ shape = 1, rate = 1, pmean = 1, psd = sqrt(1))
+```
+
+# Gamma Distribution with Shape = 2
+
+The Gamma distribution with `shape = 2` has less skewness. Here,
+the sample mean distribution converges more quickly to a normal
+distribution even for smaller sample sizes.
+
+```{r gamma-shape-2}
+demo_clt(rgamma, n = c(5, 10, 20, 40), nrep = 10000,
+ shape = 2, rate = 1, pmean = 2, psd = sqrt(2))
+```
+
+# A General Distribution Constructed from a Mixture
+
+When the population `mean` and `sd` are unspecified, the will be
+approximated by a large sample (10,000) and then used in
+standardization. For instance, consider sampling from the following
+mixture distribution.
+
+```{r mixture}
+mymix_rng <- function(n, rate = 0.5) {
+ ifelse(runif(n) < rate,
+ rgamma(n, shape = 0.5), rgamma(n, shape = 4))
+}
+
+demo_clt(mymix_rng, n = c(5, 10, 20, 40))
+
+```
+
+# Conclusion
+
+The plots above demonstrate the Central Limit Theorem in action.
+As the sample size increases, the distribution of the sample mean
+approaches a normal distribution, even for highly skewed
+underlying distributions like the Gamma distribution with
+`shape = 0.5`.
+
+This vignette illustrates the robustness of the CLT and its
+importance in statistical analysis, especially when dealing with
+non-normal data in biostatistical contexts.