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@weswc

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@weswc

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Data Assembly

Reproducibility and Organization

  • Script is a quarto document
  • Script renders free of error within the Rproject space
  • .rv$summary() present at beginning of script and passes
  • Relative paths are used
  • .Rprofile is present in same directory as final script
  • Parquet files are used where available
    Files that should be parquet:
    • [INSERT]
  • Data hash codes are printed and match source and output data
    Expected hash files:
    • [INSERT]
  • Correct source data files are read in
    Correct source data:
    • [INSERT]
  • Final dataset outputs to expected location as a csv, converts all NA values to a period, and outputs a hash
  • All code chunks are labeled
  • sessioninfo() included at the conclusion of script

yspec

  • All yspec files can be found in <project>/data/derived and are excluded from the gitignore
  • All variables have descriptions. All descriptions are easy to read and understand. All variables have units where applicable
  • All categorical variables have all options outlined and a 1:1 numerical decoded value. All categorical variables match the decoding present in the yspec
  • All continuous variables specify units and all units match those of the final dataset. If multiple analytes are included in a single column, units are clear for each analyte
  • The yspec file contains all necessary variables for analysis, including both project specific variables and NONMEM required variables

Dataset Assumptions - Automated

These can be done using pointblank and QCer can just confirm these pass!

  • List pointblank assumptions:
    • [INSERT]
  • The final dataset includes both a numeric (ID) and character (e.g. USUBJID) version of the unique subject identifier
  • The final dataset includes all columns listed in the corresponding yspec file
  • Any missing columns or observations are confirmed to be missing in source data and marked as -999
  • Missing data is documented appropriately in dataset

Data Assumptions - Manual

These can't be done using pointblank and QCer must look closely at specific sections of code

  • All manual conversions are accurate and consistent
  • All manual imputations are well documented to outside sources or sufficiently justified
  • All manual imputations are accurate according to their specified source
  • All assumptions are well justified (e.g. by the protocol, project lead decision, client decision, etc.), documented, and reasonable
  • All records to be excluded (e.g. for all analyses, for sensitivity analysis only) are properly identified, justified, and documented (i.e., CFLAG or other flag column)

Misc

  • Code is easily readable and follows general coding guidelines (link to code hub)
  • Helper functions are well documented, make sense, make reasonable assumptions, and follow good coding practices
  • Helper function arguments match as stated in yspec (e.g. SEX variable in Cockcroft-Gault equation matches decoding in yspec)

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