Prediction Model Selection and Performance Evaluation in Multiple Imputed Datasets


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Documentation for package ‘psfmi’ version 0.2.0

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D1_cox D1 method called by psfmi_cox
D1_logistic D1 method called by psfmi_lr
ipdna_md Example dataset for the psfmi_mm function
lbpmicox Example dataset for psfmi_coxr function
lbpmilr Example dataset for psfmi_lr function
lbpmilr_dev Example dataset for mivalext_lr function
lbp_orig Example dataset for psfmi_perform function, method boot_MI
mivalext_lr External Validation of logistic prediction models in multiply imputed datasets
pool_intadj Provides pooled adjusted intercept after shrinkage of pooled coefficients in multiply imputed datasets
pool_performance Pooling performance measures over multiply imputed datasets
psfmi_coxr Pooling and predictor selection function for Cox regression models in multiply imputed datasets
psfmi_D3 Meng & Rubin pooling method called by psfmi_lr
psfmi_lr Pooling and Predictor selection function for Logistic regression models in multiply imputed datasets
psfmi_mm Pooling and Predictor selection function for multilevel models in multiply imputed datasets
psfmi_mm_multiparm Multiparameter pooling methods called by psfmi_mm
psfmi_perform Evaluate performance of logistic regression models in Multiply Imputed datasets
psfmi_stab Function to evaluate bootstrap predictor and model stability in multiply imputed datasets.