Added a new function nri_cox.R for reclassification analyses of Cox
models.
Added the possibility to pool stratified Cox models in the function
psfmi_coxr.
Package 1.1.0
Added df_com to the D1 and D2 method for small sample
correction.
Update strata option in functions cv_MI and cv_MI_RR.
Package 1.0.0
Added the functions psfmi_lm, psfmi_lm_fw, psfmi_lr_bw for pooling
and backward and forward selection of linear regression models.
Added the functions glm_bw, glm_fw, coxph_bw and coxph_fw for
backward and forward selection of linear, logistic and Cox models in a
single dataset based on the likelihood ratio statistic.
Function psfmi_perform is now deprecated, use psfmi_validate
instead.
Function bw_single is now deprecated, use glm_bw instead.
Added the function hoslem_test and implemented this in the function
pool_performance.
added pooled concordance and R-squared measures for Cox regression
to function pool_performance.
Added the function pool_D2, to pool chi-square statistics.
Added the function pool_D4, to pool likelihood ratio tests.
Added the internal function pool_performance_internal, used
internally by psfmi_perform.
Option plot.indiv in function pool_performance and mivalext_lr is
deprecated, use plot.method instead.
created a new vignette for the psfmi_lm function and updated the
other ones.
corrected other bug fixes.
Updated package website with pkgdown (included citation).
Package 0.7.1
Added the functions pool_compare_models and
pool_reclassification.
applied some bug fixes in the function bw_single where selection
with anova was replaced with Anova.
added internal function RR_diff_prop to pool difference in
proportions and related SE with RR.
Updated vignettes.
Updated package website with pkgdown.
Added datasets to be used in tutorials.
Package 0.5.0
Added forward selection to the psfmi_lr and psfmi_coxr
functions.
Added the functions psfmi_lr_fw, psfmi_lr_bw, psfmi_coxr_fw and
psfmi_coxr_bw that are called by psfmi_lr or psfmi_coxr for forward and
backward selection after MI with logistic and Cox regression
models.
Extended the function psfmi_perform by including the possibility of
using cross-validation in combination with multiple imputation.
Added the functions cv_MI, cv_MI_RR, MI_cv_naive, boot_MI and
MI_boot, that are called by psfmi_perform to combine cross-validation or
bootstrapping with MI.
Added the function bw_single for backward selection in a single
dataset.
Added the functions pool_auc, rsq_nagel and scaled_brier.
Added the internal functions mean_auc_log, clean_P, miceImp.
Added the class statement smodsmi to the functions psfmi_lr,
psfmi_coxr
and psfmi_mm.
Added the following output object information to psfmi_lr,
psfmi_coxr
and psfmi_mm: model_type, predictors_in, predictors_out, fit.formula,
predictors_final and predictors_initial.