Changelog
Source:NEWS.md
cardx 0.2.2.9002
- 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.
cardx 0.2.2
CRAN release: 2024-11-27
Added a
data.frame
method toard_survival_survfit()
.Added a warning for incorrect formula type to
ard_survival_survfit()
. (#223)Implemented
summary(extend=TRUE)
inard_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()
, andard_survival_survfit.data.frame()
(and notably, not inard_survival_survfit.survfit()
).
cardx 0.2.1
CRAN release: 2024-09-03
New Features and Updates
Added S3 method
ard_total_n.survey.design()
which returns an ARD with both the survey-weighted and unweighted total sample size.Added
warning
anderror
columns toard_regression()
output. (#148)Implemented
cards::as_card()
where needed in the package to convert data frames to class ‘card’. (#200)
Bug Fixes
- Bug fix in
ard_categorical.survey.design()
where all unweighted statistics were returned, even in the case where they were explicitly not requested.
Lifecycle Changes
- The
bt(pattern)
,reformulate2(pattern_term)
,reformulate2(pattern_response)
arguments have been deprecated and are now ignored. We now usemake.names()
to determine whether a column name needs to be wrapped in backticks. (#192)
cardx 0.2.0
CRAN release: 2024-07-20
Breaking Changes
- Updated function names to follow the pattern
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()
New Features
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 the1
/TRUE
level summarized.-
Added the following functions for calculating Analysis Results Datasets (ARDs).
-
ard_stats_aov()
for calculating ANOVA results usingstats::aov()
. (#3) -
ard_stats_anova()
for calculating ANOVA results usingstats::anova()
. (#12) -
ard_stats_mcnemar_test_long()
for McNemar’s test from long data usingstats::mcnemar.test()
. -
ard_stats_prop_test()
for tests of proportions usingstats::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 usingstats::oneway.test()
. (#3) -
ard_aod_wald_test()
for calculating Wald Tests for regression models usingaod::wald.test()
. (#84) -
ard_car_anova()
for calculating ANOVA results usingcar::Anova()
. (#3) -
ard_car_vif()
for calculating the variance inflation factor usingcar::vif()
. (#10) -
ard_effectsize_cohens_d()
,ard_effectsize_paired_cohens_d()
,ard_effectsize_hedges_g()
, andard_effectsize_paired_hedges_g()
for standardized differences usingeffectsize::cohens_d()
andeffectsize::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 usingsmd::smd()
. (#4) -
ard_survival_survfit()
for survival analyses usingsurvival::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 usingsurvey::svychisq()
. (#72) -
ard_survey_svyttest()
for weighted/survey t-tests usingsurvey::svyttest()
. (#70) -
ard_survey_svyranktest()
for weighted/survey rank tests usingsurvey::svyranktest()
. (#71) -
ard_survival_survdiff()
for creating results fromsurvival::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()
, andard_stats_mood_test()
to accept multiple variables at once. Independent tests are calculated for each variable. Thevariable
argument is renamed tovariables
. (#77)Updated
ard_stats_t_test()
andard_stats_wilcox_test()
to no longer require theby
argument, which yields central estimates with their confidence intervals. (#82)Added model construction helpers,
construct_model()
,reformulate2()
,bt()
, andbt_strip()
.Imported cli call environment functions from
https://github.com/ddsjoberg/standalone/blob/main/R/standalone-cli_call_env.R
and implementedset_cli_abort_call
in user-facing functions. (#111)