Added function ard_tabulate_abnormal() to calculate
ARDs for abnormality analyses. (#310)
Adding strata argument to
ard_tabulate_max(). (#445, @jtalboys)
Added function ard_incidence_rate() to calculate
ARDs for incidence rate estimation. (#234)
The following functions have been renamed.
ard_continuous() to ard_summary()ard_categorical() to ard_tabulate()ard_dichotomous() to
ard_tabulate_value()ard_categorical_max() to
ard_tabulate_max()Updating any fmt_fn references to
fmt_fun for consistency.
Any function with an argument cardx::foo(fmt_fn) has
been updated to cardx::foo(fmt_fun). The old syntax will
continue to function, but with a deprecation warning to users.
Importantly, the ARD column named "fmt_fn" has been
updated to "fmt_fun". This change cannot be formally
deprecated. For users who were accessing the ARD object directly to
modify this column instead of using functions like
cards::update_ard_fmt_fun(), this will be a breaking
change.
Fix in ard_survival_survfit.data.frame() method
where the stratifying variable was not correctly converted back to its
original type.
Fix in ard_total_n.survey.design() to use
update() instead of dplyr::mutate(), which
sometimes caused a downstream issue.
Added function ard_stats_mantelhaen_test() to
calculate ARDs for Cochran-Mantel-Haenszel test results using
stats::mantelhaen.test(). (#238)
Added a ard_regression.data.frame() S3 method. Also
converted ard_regression_basic() to an S3 generic and added
a ard_regression_basic.data.frame() method (#287)
Specifying
ard_survfit_survfit.data.frame(variables=NULL) now creates
an unstratified survfit() model, where previously
variables argument could not be empty. (#277)
The ard_survfit_survfit.data.frame(variables) now
accepts tidyselect input. (#278)
Added conf.level and conf.type to
ard_survival_survfit() results. (#218)
Added cards::as_cards_fun() to
ard_emmeans_mean_difference() so when an error occurs the
user gets an ARD with the expected ARD structure. (#132)
ard_categorical_max() to calculate
categorical occurrence rates by maximum level per unique ID. (#240)Little n is now returned with the results of the
proportion_ci_*() functions, which then flows into the
results of ard_proportion_ci(). (#256)
Added as_cards_fun() to
ard_categorical_ci() so when there is an error, the user
gets an ARD with the expected ARD structure. (#262)
Update in ard_categorical.survey.design() for factor
variables that are all missing. These variables can now be tabulated,
where previously this resulted in an error.
Update in ard_missing.survey.design() where we can
now tabulate the missing rate of design variables, such as the
weights.
Fixed a bug in ard_survival_survfit() causing an
error when “=” character is present in stratification variable level
labels. (#252)
Bug fix in ard_categorical_ci(denominator='cell')
when missing values were present in the by
variable.
Added a data.frame method to
ard_survival_survfit().
Added a warning for incorrect formula type to
ard_survival_survfit(). (#223)
Implemented summary(extend=TRUE) in
ard_survival_survfit() to return results for time points
out of bounds. (#224)
Methods in the {survey} and {survival} packages do not retain
inputs variables types in their outputs. We now are able retain these
variable types in ARDs returned by
ard_continuous.survey.design(),
ard_categorical.survey.design(),
ard_continuous_ci.survey.design(),
ard_categorical_ci.survey.design(), and
ard_survival_survfit.data.frame() (and notably,
not in ard_survival_survfit.survfit()).
Added function ard_stats_mantelhaen_test() for
calculating ARDs for Cochran-Mantel-Haenszel test results using
stats::mantelhaen.test(). (#238)
Added S3 method ard_total_n.survey.design() which
returns an ARD with both the survey-weighted and unweighted total sample
size.
Added warning and error columns to
ard_regression() output. (#148)
Implemented cards::as_card() where needed in the
package to convert data frames to class ‘card’. (#200)
ard_categorical.survey.design() where all
unweighted statistics were returned, even in the case where they were
explicitly not requested.bt(pattern),
reformulate2(pattern_term),
reformulate2(pattern_response) arguments have been
deprecated and are now ignored. We now use make.names() to
determine whether a column name needs to be wrapped in backticks.
(#192)ard_<pkgname>_<fnname>(). This change is
immediate: previous functions names have not been deprecated.
(#106)ard_ttest() -> ard_stats_t_test()
ard_paired_ttest() -> ard_stats_paired_t_test()
ard_wilcoxtest() -> ard_stats_wilcox_test()
ard_paired_wilcoxtest() -> ard_stats_paired_wilcox_test()
ard_chisqtest() -> ard_stats_chisq_test()
ard_fishertest() -> ard_stats_fisher_test()
ard_kruskaltest() -> ard_stats_kruskal_test()
ard_mcnemartest() -> ard_stats_mcnemar_test()
ard_moodtest() -> ard_stats_mood_test()The ard_categorical_ci(value) argument has been
added. Previously, only binary variables (0/1 or TRUE/FALSE) could be
summarized. When a value is not supplied, each level of the variable is
summarized independently. By default, binary variables will have the
1/TRUE level summarized.
Added the following functions for calculating Analysis Results Datasets (ARDs).
ard_stats_aov() for calculating ANOVA results using
stats::aov(). (#3)ard_stats_anova() for calculating ANOVA results using
stats::anova(). (#12)ard_stats_mcnemar_test_long() for McNemar’s test from
long data using stats::mcnemar.test().ard_stats_prop_test() for tests of proportions using
stats::prop.test(). (#64)ard_stats_t_test_onesample() for calculating one-sample
results.ard_stats_wilcox_test_onesample() for calculating
one-sample results.ard_stats_oneway_test() for calculating ANOVA results
using stats::oneway.test(). (#3)ard_aod_wald_test() for calculating Wald Tests for
regression models using aod::wald.test(). (#84)ard_car_anova() for calculating ANOVA results using
car::Anova(). (#3)ard_car_vif() for calculating the variance inflation
factor using car::vif(). (#10)ard_effectsize_cohens_d(),
ard_effectsize_paired_cohens_d(),
ard_effectsize_hedges_g(), and
ard_effectsize_paired_hedges_g() for standardized
differences using effectsize::cohens_d() and
effectsize::hedges_g(). (#50)ard_emmeans_mean_difference() for calculating the
least-squares mean differences using the {emmeans} package. (#34)ard_smd_smd() for calculating standardized mean
differences using smd::smd(). (#4)ard_survival_survfit() for survival analyses using
survival::survfit(). (#43)ard_continuous.survey.design() for calculating
univariate summary statistics from weighted/survey data using many
functions from the {survey} package. (#68)ard_categorical.survey.design() for tabulating summary
statistics from weighted/survey data using many functions from the
{survey} package. (#140)ard_dichotomous.survey.design() for tabulating
dichotomous summary statistics from weighted/survey data using many
functions from the {survey} package. (#2)ard_missing.survey.design() for tabulating missing
summary statistics from weighted/survey data using many functions from
the {survey} package. (#2)ard_attributes.survey.design() for summarizing labels
and attributes from weighted/survey data using many functions from the
{survey} package.ard_survey_svychisq() for weighted/survey chi-squared
test using survey::svychisq(). (#72)ard_survey_svyttest() for weighted/survey t-tests using
survey::svyttest(). (#70)ard_survey_svyranktest() for weighted/survey rank tests
using survey::svyranktest(). (#71)ard_survival_survdiff() for creating results from
survival::survdiff(). (#113)ard_regression_basic() for basic regression models. The
function focuses on matching model terms to underlying variables names.
(#46)Updated functions ard_stats_t_test(),
ard_stats_paired_t_test(),
ard_stats_wilcox_test(),
ard_stats_paired_wilcox_test(),
ard_stats_chisq_test(),
ard_stats_fisher_test(),
ard_stats_kruskal_test(),
ard_stats_mcnemar_test(), and
ard_stats_mood_test() to accept multiple variables at once.
Independent tests are calculated for each variable. The
variable argument is renamed to variables.
(#77)
Updated ard_stats_t_test() and
ard_stats_wilcox_test() to no longer require the
by argument, which yields central estimates with their
confidence intervals. (#82)
Added model construction helpers, construct_model(),
reformulate2(), bt(), and
bt_strip().
Imported cli call environment functions from
https://github.com/ddsjoberg/standalone/blob/main/R/standalone-cli_call_env.R
and implemented set_cli_abort_call in user-facing
functions. (#111)