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_pkgdown.yml
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93 lines (88 loc) · 2.34 KB
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url: https://boyercb.github.io/cfperformance/
template:
bootstrap: 5
bootswatch: flatly
home:
title: cfperformance
description: Counterfactual Prediction Model Performance Estimation
authors:
Christopher Boyer:
href: https://github.com/boyercb
Issa Dahabreh:
href: https://www.hsph.harvard.edu/issa-dahabreh/
Jon Steingrimsson:
href: https://vivo.brown.edu/display/jsteingr
navbar:
structure:
left: [intro, reference, articles, news]
right: [search, github]
components:
articles:
text: Articles
menu:
- text: Introduction to cfperformance
href: articles/introduction.html
- text: Transportability Analysis
href: articles/transportability.html
- text: Machine Learning Integration
href: articles/ml-integration.html
reference:
- title: Counterfactual Performance (Single Population)
desc: Estimate prediction model performance under counterfactual interventions
contents:
- cf_mse
- cf_auc
- cf_calibration
- cf_sensitivity
- cf_specificity
- cf_fpr
- cf_roc
- title: Transportability (Two Populations)
desc: Transport prediction model performance from source to target population
contents:
- tr_mse
- tr_auc
- tr_calibration
- tr_sensitivity
- tr_specificity
- tr_fpr
- tr_roc
- title: Model Selection
desc: Cross-validation and model comparison
contents:
- cf_cv
- cf_compare
- title: Machine Learning
desc: ML learner specifications for nuisance models
contents:
- ml_learner
- print.ml_learner
- title: Nuisance Models
desc: Fit propensity and outcome models
contents:
- fit_nuisance
- title: S3 Methods
desc: Methods for result objects
contents:
- as.data.frame.tr_roc
- coef.cf_performance
- coef.tr_performance
- confint.cf_performance
- confint.tr_performance
- plot.cf_auc
- plot.cf_calibration
- plot.tr_calibration
- plot.tr_roc
- print.cf_compare
- print.cf_cv
- print.cf_nuisance
- print.cf_performance
- print.tr_performance
- summary.cf_compare
- summary.cf_cv
- summary.cf_performance
- summary.tr_performance
- title: Example Data
contents:
- cvd_sim
- transport_sim