Package: psfmi 1.4.0

psfmi: Prediction Model Pooling, Selection and Performance Evaluation Across Multiply Imputed Datasets

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) <doi:10.1186/s12874-017-0404-7>. Wiel (2009) <doi:10.1093/biostatistics/kxp011>. Marshall (2009) <doi:10.1186/1471-2288-9-57>.

Authors:Martijn Heymans [cre, aut], Iris Eekhout [ctb]

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NEWS

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

Peer review:

Bug tracker:https://github.com/mwheymans/psfmi/issues

Datasets:
  • anderson - Data from a placebo-controlled RCT with leukemia patients
  • aortadis - Dataset of patients with a aortadissection
  • bmd - Data of a non-experimental study in more than 300 elderly women
  • chlrform - Data about concentration of ß2-microglobuline in urine as indicator for possible damage to the kidney
  • chol_long - Long dataset of persons from the The Amsterdam Growth and Health Longitudinal Study
  • chol_wide - Wide dataset of persons from the The Amsterdam Growth and Health Longitudinal Study
  • day2_dataset4_mi - Dataset of low back pain patients with missing values
  • hipstudy - Dataset of elderly patients with a hip fracture
  • hipstudy_external - External Dataset of elderly patients with a hip fracture
  • hoorn_basic - Dataset of the Hoorn Study
  • infarct - Data of a patient-control study regarding the relationship between MI and smoking
  • ipdna_md - Example dataset for the psfmi_mm function
  • lbp_orig - Example dataset for psfmi_perform function, method boot_MI
  • lbpmi_extval - Example dataset of Low Back Pain Patients for external validation
  • lbpmicox - Example dataset for psfmi_coxr function
  • lbpmilr - Example dataset for psfmi_lr function
  • lbpmilr_dev - Example dataset for mivalext_lr function
  • lungvolume - Data of the development of lung and heartvolume of unborn babies
  • mammaca - Data of a study among women with breast cancer
  • men - Data of 613 patients with meningitis
  • sbp_age - Dataset with blood pressure measurements
  • sbp_qas - Dataset with blood pressure measurements
  • smoking - Survival data about smoking
  • weight - Dataset of persons from the The Amsterdam Growth and Health Longitudinal Study

On CRAN:

cox-regressionimputationimputed-datasetslogisticmultiple-imputationpoolpredictorregressionselectionsplinespline-predictors

7.13 score 9 stars 71 scripts 506 downloads 7 mentions 48 exports 142 dependencies

Last updated 1 years agofrom:6afb51f1f1. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 09 2024
R-4.5-winOKOct 09 2024
R-4.5-linuxOKOct 09 2024
R-4.4-winOKOct 09 2024
R-4.4-macOKOct 09 2024
R-4.3-winOKAug 10 2024
R-4.3-macOKAug 10 2024

Exports:boot_MIbw_singleclean_Pcoxph_bwcoxph_fwcv_MIcv_MI_RRglm_bwglm_fwhoslem_testkm_estimateskm_fitmean_auc_logMI_bootMI_cv_naivemiceImpmivalext_lrnri_coxnri_estpool_aucpool_compare_modelspool_D2pool_D4pool_intadjpool_performancepool_performance_internalpool_reclassificationpool_RRpsfmi_coxrpsfmi_coxr_bwpsfmi_coxr_fwpsfmi_lmpsfmi_lm_bwpsfmi_lm_fwpsfmi_lrpsfmi_lr_bwpsfmi_lr_fwpsfmi_mmpsfmi_mm_multiparmpsfmi_performpsfmi_stabpsfmi_validaterisk_coxphRR_diff_proprsq_nagelrsq_survscaled_brierstab_single

Dependencies:abindbackportsbase64encbitbit64bitopsbootbroombslibcachemcarcarDatacaToolscheckmateclicliprclustercodetoolscolorspacecowplotcpp11crayoncvAUCdata.tableDBIDerivdigestdoBydplyrevaluatefansifarverfastmapfontawesomeforcatsforeachforeignFormulafsfurrrfuturegenericsggplot2glmnetglobalsgluegplotsgridExtragtablegtoolshavenhighrHmischmshtmlTablehtmltoolshtmlwidgetsisobanditeratorsjomojquerylibjsonliteKernSmoothknitrlabelinglatticelifecyclelistenvlme4magrittrMASSMatrixMatrixModelsmemoisemgcvmicemicrobenchmarkmimeminqamitmlmitoolsmodelrmultcompmunsellmvtnormnlmenloptrnnetnormnumDerivordinalpanparallellypbkrtestpillarpkgconfigplyrpolsplineprettyunitspROCprogresspurrrquantregR6rappdirsRColorBrewerRcppRcppEigenreadrrlangrmarkdownrmsROCRrpartrsamplerstudioapisandwichsassscalesshapesliderSparseMstringistringrsurvivalTH.datatibbletidyrtidyselecttinytextzdbucminfutf8vctrsviridisviridisLitevroomwarpwithrxfunyamlzoo

Pool Model Performance

Rendered fromPool_Model_Performance.Rmdusingknitr::rmarkdownon Oct 09 2024.

Last update: 2023-06-17
Started: 2021-09-23

Pooling and Selection of Cox Regression Models

Rendered frompsfmi_CoxModels.Rmdusingknitr::rmarkdownon Oct 09 2024.

Last update: 2023-06-15
Started: 2020-06-30

Pooling and Selection of Linear Regression Models

Rendered frompsfmi_LinearModels.Rmdusingknitr::rmarkdownon Oct 09 2024.

Last update: 2021-08-29
Started: 2021-08-29

Pooling and Selection of Logistic Regression Models

Rendered frompsfmi_LogisticModels.Rmdusingknitr::rmarkdownon Oct 09 2024.

Last update: 2021-08-29
Started: 2020-06-30

Pooling AUC values

Rendered fromPooling_AUC_values.Rmdusingknitr::rmarkdownon Oct 09 2024.

Last update: 2023-06-17
Started: 2021-09-23

Working together: mice and psfmi

Rendered frompsfmi_mice.Rmdusingknitr::rmarkdownon Oct 09 2024.

Last update: 2021-08-29
Started: 2020-07-01

Readme and manuals

Help Manual

Help pageTopics
Data from a placebo-controlled RCT with leukemia patientsanderson
Dataset of patients with a aortadissectionaortadis
Data of a non-experimental study in more than 300 elderly womenbmd
Predictor selection function for backward selection of Linear and Logistic regression models.bw_single
Data about concentration of ß2-microglobuline in urine as indicator for possible damage to the kidneychlrform
Long dataset of persons from the The Amsterdam Growth and Health Longitudinal Study (AGHLS)chol_long
Wide dataset of persons from the The Amsterdam Growth and Health Longitudinal Study (AGHLS)chol_wide
Predictor selection function for backward selection of Cox regression models in single complete dataset.coxph_bw
Predictor selection function for forward selection of Cox regression models in single complete dataset.coxph_fw
Dataset of low back pain patients with missing valuesday2_dataset4_mi
Function for backward selection of Linear and Logistic regression models.glm_bw
Function for forward selection of Linear and Logistic regression models.glm_fw
Dataset of elderly patients with a hip fracturehipstudy
External Dataset of elderly patients with a hip fracturehipstudy_external
Dataset of the Hoorn Studyhoorn_basic
Calculates the Hosmer and Lemeshow goodness of fit test.hoslem_test
Data of a patient-control study regarding the relationship between MI and smokinginfarct
Example dataset for the psfmi_mm functionipdna_md
Kaplan-Meier risk estimates for Net Reclassification Index analysiskm_estimates
Kaplan-Meier (KM) estimate at specific time pointkm_fit
Example dataset for psfmi_perform function, method boot_MIlbp_orig
Example dataset of Low Back Pain Patients for external validationlbpmi_extval
Example dataset for psfmi_coxr functionlbpmicox
Example dataset for psfmi_lr functionlbpmilr
Example dataset for mivalext_lr functionlbpmilr_dev
Data of the development of lung and heartvolume of unborn babieslungvolume
Data of a study among women with breast cancermammaca
Data of 613 patients with meningitismen
External Validation of logistic prediction models in multiply imputed datasetsmivalext_lr
Net Reclassification Index for Cox Regression Modelsnri_cox
Calculation of Net Reclassification Index measuresnri_est
Calculates the pooled C-statistic (Area Under the ROC Curve) across Multiply Imputed datasetspool_auc
Compare the fit and performance of prediction models across Multipy Imputed datapool_compare_models
Combines the Chi Square statistics across Multiply Imputed datasetspool_D2
Pools the Likelihood Ratio tests across Multiply Imputed datasets ( method D4)pool_D4
Provides pooled adjusted intercept after shrinkage of pooled coefficients in multiply imputed datasetspool_intadj
Pooling performance measures across multiply imputed datasetspool_performance
Function to pool NRI measures over Multiply Imputed datasetspool_reclassification
Function to combine estimates by using Rubin's Rulespool_RR
Pooling and Predictor selection function for backward or forward selection of Cox regression models across multiply imputed data.psfmi_coxr
Pooling and Predictor selection function for backward or forward selection of Linear regression models across multiply imputed data.psfmi_lm
Pooling and Predictor selection function for backward or forward selection of Logistic regression models across multiply imputed data.psfmi_lr
Pooling and Predictor selection function for multilevel models in multiply imputed datasetspsfmi_mm
Multiparameter pooling methods called by psfmi_mmpsfmi_mm_multiparm
Internal validation and performance of logistic prediction models across Multiply Imputed datasetspsfmi_perform
Function to evaluate bootstrap predictor and model stability in multiply imputed datasets.psfmi_stab
Internal validation and performance of logistic prediction models across Multiply Imputed datasetspsfmi_validate
Risk calculation at specific time point for Cox modelrisk_coxph
Nagelkerke's R-square calculation for logistic regression / glm modelsrsq_nagel
R-square calculation for Cox regression modelsrsq_surv
Dataset with blood pressure measurementssbp_age
Dataset with blood pressure measurementssbp_qas
Calculates the scaled Brier scorescaled_brier
Survival data about smokingsmoking
Function to evaluate bootstrap predictor and model stability.stab_single
Dataset of persons from the The Amsterdam Growth and Health Longitudinal Study (AGHLS)weight