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confint_level #58confint_level #58confint_sep = " to ".confint_sep = " to ".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().or_plot() and hr_plot() introduced
in 0.9.2 because of new total column specification.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
micelmuni(), lmmulti(),
lmmixed(), glmuni(), glmmulti(),
glmmixed(), coxphuni(),
coxphmulti()metrics_hoslem() is the first of a number of ‘metrics’
functions which will be introduced.These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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