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.