Pooling, backward and forward selection of logistic and Cox regression models in multiply imputed datasets. Backward and forward selection can be done from the pooled model using Rubin's Rules (RR), the D1, D2, D3 and the median p-values method. This is also possible for Mixed models. The models can contain continuous, dichotomous, categorical and restricted cubic spline predictors and interaction terms between all these type of predictors. The stability of the models can be evaluated using bootstrapping and cluster bootstrapping. The package further contains functions to pool the model performance as ROC/AUC, R-squares, scaled Brier score and calibration plots for logistic regression models. Internal validation can be done with cross-validation or bootstrapping. The adjusted intercept after shrinkage of pooled regression coefficients can be obtained. Backward and forward selection as part of internal validation is possible. Also a function to externally validate logistic prediction models in multiple imputed datasets is available. Eekhout (2017) <doi:10.1186/s12874-017-0404-7>. Wiel (2009) <doi:10.1093/biostatistics/kxp011>. Marshall (2009) <doi:10.1186/1471-2288-9-57>.
Version: | 0.5.0 |
Depends: | R (≥ 3.6.0) |
Imports: | survival (> 2.41-3), car (> 3.0.0), lme4 (≥ 1.1-21), norm (≥ 1.0-9.5), miceadds (> 2.10-14), mitools (≥ 2.4), pROC (> 1.11.0), rms (> 5.1-2), ResourceSelection (> 0.3-2), ggplot2 (> 2.2.1), dplyr (≥ 0.8.3), magrittr (≥ 1.5), rsample (≥ 0.0.5), purrr (≥ 0.3.3), tidyr (≥ 1.0.0), tibble (≥ 2.1.3), mice (≥ 3.6.0), mitml (≥ 0.3-7), cvAUC (≥ 1.1.0), stringr (≥ 1.4.0) |
Suggests: | foreign (≥ 0.8-72), knitr, rmarkdown, testthat, bookdown, readr |
Published: | 2020-09-24 |
Author: | Martijn Heymans |
Maintainer: | Martijn Heymans <mw.heymans at amsterdamumc.nl> |
BugReports: | https://github.com/mwheymans/psfmi/issues |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | https://mwheymans.github.io/psfmi/ |
NeedsCompilation: | no |
Materials: | README NEWS |
In views: | MissingData |
CRAN checks: | psfmi results |
Reference manual: | psfmi.pdf |
Vignettes: |
MI_boot MI_cv_naive boot_MI cv_MI cv_MI_RR psfmi_CoxModels psfmi_LogisticModels psfmi_StabilityAnalysis psfmi_mice psfmi_valext |
Package source: | psfmi_0.5.0.tar.gz |
Windows binaries: | r-devel: psfmi_0.5.0.zip, r-release: psfmi_0.5.0.zip, r-oldrel: psfmi_0.5.0.zip |
macOS binaries: | r-release: psfmi_0.5.0.tgz, r-oldrel: psfmi_0.5.0.tgz |
Old sources: | psfmi archive |
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