Other packages > Find by keyword >

psfmi  

Prediction Model Pooling, Selection and Performance Evaluation Across Multiply Imputed Datasets
View on CRAN: Click here


Download and install psfmi package within the R console
Install from CRAN:
install.packages("psfmi")

Install from Github:
library("remotes")
install_github("cran/psfmi")

Install by package version:
library("remotes")
install_version("psfmi", "1.4.0")



Attach the package and use:
library("psfmi")
Maintained by
Martijn Heymans
[Scholar Profile | Author Map]
First Published: 2019-05-16
Latest Update: 2023-06-17
Description:
Pooling, backward and forward selection of linear, 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, D4 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 (cluster) bootstrapping. The package further contains functions to pool model performance measures as ROC/AUC, Reclassification, R-squared, scaled Brier score, H&L test and calibration plots for logistic regression models. Internal validation can be done across multiply imputed datasets 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. A function to externally validate logistic prediction models in multiple imputed datasets is available and a function to compare models. For Cox models a strata variable can be included. Eekhout (2017) . Wiel (2009) . Marshall (2009) .
How to cite:
Martijn Heymans (2019). psfmi: Prediction Model Pooling, Selection and Performance Evaluation Across Multiply Imputed Datasets. R package version 1.4.0, https://cran.r-project.org/web/packages/psfmi. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.1.0 (2019-05-16 13:50), 0.2.0 (2020-02-03 08:30), 0.5.0 (2020-09-24 14:30), 0.7.1 (2021-01-13 17:40), 1.0.0 (2021-09-23 12:10), 1.1.0 (2022-11-06 16:50), 1.3.0 (2023-06-16 09:10)
Other packages that cited psfmi R package
View psfmi citation profile
Other R packages that psfmi depends, imports, suggests or enhances
Complete documentation for psfmi
Functions, R codes and Examples using the psfmi R package
Some associated functions: MI_boot . MI_cv_naive . RR_diff_prop . anderson . aortadis . bmd . boot_MI . bw_single . chlrform . chol_long . chol_wide . clean_P . coxph_bw . coxph_fw . cv_MI . cv_MI_RR . day2_dataset4_mi . glm_bw . glm_fw . hipstudy . hipstudy_external . hoorn_basic . hoslem_test . infarct . ipdna_md . km_estimates . km_fit . lbp_orig . lbpmi_extval . lbpmicox . lbpmilr . lbpmilr_dev . lungvolume . mammaca . mean_auc_log . men . miceImp . mivalext_lr . nri_cox . nri_est . pool_D2 . pool_D4 . pool_RR . pool_auc . pool_compare_models . pool_intadj . pool_performance . pool_performance_internal . pool_reclassification . psfmi_coxr . psfmi_coxr_bw . psfmi_coxr_fw . psfmi_lm . psfmi_lm_bw . psfmi_lm_fw . psfmi_lr . psfmi_lr_bw . psfmi_lr_fw . psfmi_mm . psfmi_mm_multiparm . psfmi_perform . psfmi_stab . psfmi_validate . risk_coxph . rsq_nagel . rsq_surv . sbp_age . sbp_qas . scaled_brier . smoking . stab_single . weight . 
Some associated R codes: MI_boot.R . MI_cv_naive.R . RR_diff_prop.R . boot_MI.R . bw_single.R . clean_P.R . coxph_bw.R . coxph_fw.R . cv_MI.R . cv_MI_RR.R . glm_bw.R . glm_fw.R . hoslem_test.R . km_estimates.R . km_fit.R . lbpmi_extval.R . mean_auc_log.R . miceImp.R . mivalext_lr.R . nri_cox.R . nri_est.R . pool_D2.R . pool_D4.R . pool_RR.R . pool_auc.R . pool_compare_models.R . pool_intadj.R . pool_performance.R . pool_performance_internal.R . pool_reclassification.R . psfmi_coxr.R . psfmi_coxr_bw.R . psfmi_coxr_fw.R . psfmi_lm.R . psfmi_lm_bw.R . psfmi_lm_fw.R . psfmi_lr.R . psfmi_lr_bw.R . psfmi_lr_fw.R . psfmi_mm.R . psfmi_mm_multiparm.R . psfmi_perform.R . psfmi_stab.R . psfmi_validate.R . risk_coxph.R . rsq_nagel.R . rsq_surv.R . scaled_brier.R . stab_single.R .  Full psfmi package functions and examples
Downloads during the last 30 days
02/2702/2803/0103/0203/0303/0403/0503/0603/0703/0803/0903/1003/1103/1203/1303/1403/1503/1603/1703/1803/1903/2003/2103/2203/2303/2403/2503/2603/2703/28Downloads for psfmi24681012141618202224262830TrendBars

Today's Hot Picks in Authors and Packages

landmix  
Landmark Prediction for Mixture Data
Non-parametric prediction of survival outcomes for mixture data that incorporates covariates and a l ...
Download / Learn more Package Citations See dependency  
gglgbtq  
Show Pride on 'ggplot2' Plots
Provides multiple palettes based on pride flags with tailored themes. ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  

23,842

R Packages

207,311

Dependencies

64,420

Author Associations

23,781

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA