Package: predRupdate 0.2.1.9000

predRupdate: Prediction Model Validation and Updating

Evaluate the predictive performance of an existing (i.e. previously developed) prediction/ prognostic model given relevant information about the existing prediction model (e.g. coefficients) and a new dataset. Provides a range of model updating methods that help tailor the existing model to the new dataset; see Su et al. (2018) <doi:10.1177/0962280215626466>. Techniques to aggregate multiple existing prediction models on the new data are also provided; see Debray et al. (2014) <doi:10.1002/sim.6080> and Martin et al. (2018) <doi:10.1002/sim.7586>).

Authors:Glen P. Martin [aut, cre, cph], David Jenkins [aut, cph], Matthew Sperrin [aut, cph]

predRupdate_0.2.1.9000.tar.gz
predRupdate_0.2.1.9000.zip(r-4.7-any)predRupdate_0.2.1.9000.zip(r-4.6-any)predRupdate_0.2.1.9000.zip(r-4.5-any)
predRupdate_0.2.1.9000.tgz(r-4.6-any)predRupdate_0.2.1.9000.tgz(r-4.5-any)
predRupdate_0.2.1.9000.tar.gz(r-4.7-any)predRupdate_0.2.1.9000.tar.gz(r-4.6-any)
predRupdate_0.2.1.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
predRupdate/json (API)

# Install 'predRupdate' in R:
install.packages('predRupdate', repos = c('https://glenmartin31.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/glenmartin31/predrupdate/issues

Pkgdown/docs site:https://glenmartin31.github.io

Datasets:
  • SYNPM - SYNthetic Prediction Models (SYNPM) and Validation dataset

On CRAN:

Conda:

5.66 score 9 stars 17 scripts 280 downloads 10 exports 77 dependencies

Last updated from:6341cb708e. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK181
source / vignettesOK273
linux-release-x86_64OK166
macos-release-arm64OK99
macos-oldrel-arm64OK114
windows-develOK104
windows-releaseOK109
windows-oldrelOK115
wasm-releaseOK132

Exports:dummy_varsinv_logitlogitmap_newdatapred_input_infopred_predictpred_stacked_regressionpred_updatepred_val_probspred_validate

Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecorrplotcowplotcpp11DerivdoBydplyrfarverforecastFormulafracdiffgenericsggplot2ggpubrggrepelggsciggsignifgluegridExtragtableisobandlabelinglatticelifecyclelme4lmtestmagrittrMASSMatrixMatrixModelsmgcvminqamodelrnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigpolynompROCpurrrquantregR6rbibutilsRColorBrewerRcppRcppArmadilloRcppEigenRdpackreformulasrlangrstatixS7scalesSparseMstringistringrsurvivaltibbletidyrtidyselecttimeDateurcautf8vctrsviridisLitewithrzoo

Introduction to the predRupdate package
Preamble | Data | Example 1: validating an existing prediction model on new data | Survival analysis model | Specifying the baseline cumulative hazard | A note on basehaz() in R | Example 2: model updating on new data | Example 3: model aggregation on new data | A note on structure of new_data
Rendered frompredRupdate.Rmdusingknitr::rmarkdown

Last update: 2024-08-23
Started: 2023-03-31

Example of Validating a Model that Includes Spline Terms
Preamble | Data | External Validation
Rendered frompredRupdate_splineIllustration.Rmdusingknitr::rmarkdown

Last update: 2023-11-20
Started: 2023-11-20

Technical Background to predRupdate
Preamble | Clinical Prediction Models | Predictive Performance Metrics | Calibration | Discrimination | Overall Accuracy | Model Updating Methods | Model Aggregation Methods | References
Rendered frompredRupdate_technical.Rmdusingknitr::rmarkdown

Last update: 2023-04-26
Started: 2023-03-31