NEWS.md
ff_expand() approach for model simulation added.or_plot() and coefficient_plot() now allowing confidence interval specification via confint_level #58ff_label() to convert input to dataframe.ff_label() to convert input to dataframe.fit2df.lmerMod() set default confint_sep = " to ".boot_predict() and boot_compare() confidence interval limits and methods options added.fit2df.lmerMod() set default confint_sep = " to ".boot_predict() and boot_compare() confidence interval limits and methods options added.cont_cut argument in finalfit(). #78summary_factorlist().coefficient_plot() when passing lmmixed() object.finalfit().lmuni(), lmmulti(), glmuni(), glmmulti(), coxphuni(), coxphmulti().cont_cut argument in finalfit(). #78summary_factorlist().coefficient_plot() when passing lmmixed() object.finalfit().lmuni(), lmmulti(), glmuni(), glmmulti(), coxphuni(), coxphmulti().finalfit() and summary_factorlist().summary_factorlist() for weighted tables.finalfit() updated and arguments to underlying models can now be passed directly.missing_plot() bugs fixed, many thanks @nathansam. #72finalfit() for CPH models now provides column proportions by default, many thanks corneliushennch. #74summary_factorlist_stratified(): beta testing for stratified tables.rm_empty_block() added: remove rows where all specified variables are missing.add_row_total in summary_factorlist() now can include proportion of complete data via include_row_totals_percent argument.coxphmulti().summary_factorlist(): non-parametric continuous variables now defaults to Q1 - Q3 rather than single figure IQR.ff_interaction(): default factor separator changed from “|” to “_” and variable separator from “__” to “_” given incompatibilities with packages such as brms.coefficient_plot() fixed to bring back point estimates.na_to_prop = FALSE in summary_factorlist() to not include missing data in column proportions of categorical data.ff_relabel_df() added to allow passing data frame / tibble with labels directly at bottom of pipe.ff_relabel() tightened to allow mismatch between available data and labels.missing_compare() code updated to allow arguments to be passed to new summary_factorlist().I(var1^2) etc.) are now better supported in finalfit().cluster(), frailty() and strata() terms shown in finalfit() regression tables as an indicator they have been included in model.or_plot() remove_ref bug fix.ff_newdata() bug fix.remove_ref argument.summary_factorlist() completely rewritten. New column and row summary functions. Alternative statistical tests included. Finer control over continuous variable behaviours.fit2df() function for mipo objects. See missing data vignette/article for examples.finalfit() table by including keep_fit_id = TRUE. See ff_merge() documentation for details.tidyr::spread() in summary_factorlist() so updated to tidyr::pivot_wider().ff_column_totals() added to be used in combination with summary_factorlist().ff_row_totals() added to be used in combination with summary_factorlist().ff_percent_only() added to be used in combination with summary_factorlist(). #25ff_remove_p() can be applied to any condensed finalfit output to remove the p-value. #26finalfit() now takes column = FALSE to provide row proportions. #26check_recode() added.remove_labels() now works for tibbles. #28summary_factorlist() includes argument cont_range = TRUE to include quartiles Q1 and Q3 when median for continuous variables. #29data(wcgs) added.summary_factorlist() geometric sd added.ff_label() now does not add class “labelled”.glmmulti() and lmmulti() to run multiple models from multiple dependent variables. It wasn’t used and the list generated was inconvenient for passing output to other functions such as ggfortify::autoplot().ff_permute() re-written to allow many more options for producing intermediate models.coxphuni() and coxphmulti() now take the other library(survival) functions survival::strata() and survival::cluster().hr_plot() axis title edit option.remove_ref = TRUE) to or_plot(), hr_plot() and coefficient_plot().summary_factorlist() digit rounding option added.summary_factorlist() geometric mean option added.or_plot(), hr_plot() and coeffient_plot().cmprsk::crr(): crruni(), crrmulti() and fit2df().library(survey): svyglmuni(), svyglmmulti() provide support for. #13summary_factorlist() total column now summarises continuous variables. #17 #21summary_factorlist() can now take any Hmisc:::summary.formula argument, such as catTest = catTestfisher.catTestfisher() added.finalfit_permute() added.glmuni(), glmmulti(), lmuni(), lmmulti() now all take weights and any other glm() or lm() argument. #13summary_factorlist() rework. Now supports any number of factor levels in dependent. #14 #15summary_factorlist() now provides total count for continuous variable. #17or_plot() bug fixff_remove_ref() added. #12glmmixed() and lmmixed() now support random gradient models, and all complex lme4 specifications.ff_plot() addedcoefficient_plot() addedvariable_type() addedshinyfit started.ff_relabel() added.finalfit() for not-allowed colons (:) in factor levels. #10ff_glimpse() re-written to remove psych dependencymissing_glimpse() added: single data frame describing all variables and missing valuesff_interaction() added: create variable for an interaction between two factorsff_label() added: easily add label to variable in dataframeff_newdata() modified to take dataframe without requirement for dependent and explanatory argumentssummary_factorlist() modified to allow user to change number of unique factor levels at which a variable a continuous variable is converted to a factor (cont_cut). #9fit2df() and its internal function extract_fit modified to take confint_type and confint_level.missing_predictorMatrix() added for use with mice
metrics_hoslem() is the first of a number of ‘metrics’ functions which will be introduced.