High-Performance Open-Source Archive
svyCreateTableOneJS /
svyCreateTableOne2 now display integer counts (no
.0 suffix) when n_original = TRUE. Previously,
categorical variable frequencies and the n row were formatted as floats
(e.g., 12345.0) even after replacing weighted counts with
original data.svyCreateTableOne2 now correctly
labels the “Overall” column when using addOverall = TRUE
with Labels = TRUE. Previously, the “Overall” header was
missing, causing column name misalignment.TableSubgroupGLM /
TableSubgroupMultiGLM now fully support
family = "quasibinomial" for survey-weighted logistic
regression. Previously, "quasibinomial" was not mapped to
quasibinomial() for svyglm, exp() was not
applied to coefficients, and the column was not named “OR”.TableSubgroupGLM /
TableSubgroupMultiGLM now automatically convert factor
outcomes to numeric (0/1) for survey data with binomial/quasibinomial
family. Previously, factor outcomes caused
"'-' not meaningful for factors" error with
svyglm.count_event_by_glm now handles
data.table input correctly by converting to
data.frame before column subsetting. Previously,
data.table objects from
survey.design$variables caused
"column name 'required_vars' is not found" error.deparse(formula)
with deparse1(formula) in TableSubgroupGLM,
TableSubgroupMultiGLM, TableSubgroupCox, and
TableSubgroupMultiCox to suppress
"Using formula(x) is deprecated when x is a character vector of length > 1"
warnings with long formulas.svyCreateTableOneJS /
svyCreateTableOne2 now display actual sample sizes in the
n row instead of weighted totals when
n_original = TRUE. Previously, the n row
showed the sum of survey weights (e.g., 181,174,390) instead of the
original sample count (e.g., 23,641). Supports no-strata, single-strata,
and compound-strata cases..display functions
(cox2.display, svycox.display,
svyregress.display, geeglm.display,
lmer.display) now correctly handle models with interaction
terms (e.g., a*b or a:b). This prevents
dimension dropping or row matching errors during formatting.glmshow.display now correctly
preserves the offset term (e.g.,
offset(log(n))) when calculating crude estimates. This
ensures statistically accurate univariate results for Poisson and other
GLM models by maintaining the same exposure baseline.svyregress.display no longer errors when
pcut.univariate selects a single variable (prevents
dimension dropping).svycox.display now preserves matrix dimensions
when subsetting to a single selected term with
pcut.univariate.CreateTableOneJS and CreateTableOne2
now have correct headers for overall and strata columns.TableSubgroupCox and
TableSubgroupMultiCox now correctly maintain Count and
Percent from original data in competing risk analysisdata_original is provided, Count and Percent are
calculated from the original data instead of finegray-transformed
dataTableSubgroupCox and
TableSubgroupMultiCox now support competing risk analysis
with proper cumulative incidence calculationdata_original and formula_original
parameters to TableSubgroupCox and
TableSubgroupMultiCox for competing risk analysissurvfit() with
factor event variable on the original datacox2.display now properly handles multi-state
models automatically without the msm parameter.event_msm is
applied,cox2.display only returns the output with the
selected variables.TableSubgroupMultiCox now correctly extracts
p-values from survey Cox models (svycoxph) by using the last column
index instead of hardcoded column 5cox2.display now correctly handles
strata() terms in coxph modelscox2.display now properly handles variables with
no variation in complete cases during univariate analysiscox2.display correctly filters out NA p-values
when using pcut.univariate optioncox2.display now properly handles data.table
objects with data_for_univariate parametercox2.display shows adjusted HR properly and also
handles clustered coxph model properly.pcut.univariate is applied,
cox2.display now correctly shows metrics (N, AIC, C-index,
Events) from the selected model with significant variables@importFrom survival Surv for proper
NAMESPACE generationglmshow.display now properly handles interaction
terms with pcut.univariate optionglmshow.display correctly maintains variable order
when selecting significant variables with interaction termsglmshow.display now displays proper reference
levels for interaction terms with multi-level factors (e.g., “wt:cyl:
ref.=4”)geeglm.display now correctly uses
data_for_univariate with pcut.univariate to
refit model with selected variables only, updating N accordinglylmer.display now correctly uses
data_for_univariate with pcut.univariate to
refit model with selected variables only, updating N and other metrics
accordinglyLabeljsTable now supports interaction terms,
applying labels to both main effects and interaction coefficientsCreateTableOneJS and
svyCreateTableOneJS, column names are more descriptive when
using psub = T with strata,
strata2.data_for_univariate in
cox2.display, geeglm.display,
lmer.display, crude p-values in univariate tables are now
computed directly from the raw data passed via
data_for_univariate.cox2.display when all status 0cox2.display when all status 0
(isList, column&row name diff check)id and weight
columns from input data in the Cox module.labeldata option in
TableSubgroupGLM, TableSubgroupMultiGLM,
TableSubgroupCox, TableSubgroupMultiCoxcox2.display HRTableSubgroupMultiGLM when
covariatesforestcox when categorical binary
outcomeforestglm when categorical
covariatesforestcox and forestglm with
datatype of P value in tableforestcoxforestcoxaddOverall options to
svyCreateTableOneJSTableSubgroupCoxweights option to
TableSubgroupCox and TableSubgroupMultiCox for
marginal cox model. ex: weights = "weights"strata option to
TableSubgroupCox and TableSubgroupMultiCox for
marginal cox model. ex: strata = "sex"TableSubgroupMultiCox with clusterTableSubgroupCox and
TableSubgroupMultiCoxcox2.display.cluster option to
TableSubgroupCox and TableSubgroupMultiCox for
marginal cox model. ex: cluster = "inst"forestcox and forestglm.svycox and
svyglm.lmer.coxme.cox2.glmshow.normalityTest option to
CreateTableOneJS to perform the Shapiro test for all
variables.glmshow.display
and TableSubgroupMultiGLMmortTableSubgroupGLM: thanks for
weisx2022TableSubgroupCox: thanks for
ciciingsvyglm ( thanks
for cyk0315)addOverall options to CreateTableOneJS
and svyCreateTableOneJS to add overall column.mk.levLabelepiDisplay: thanks for
thisis05TableSubgroupCox: thanks for
Ding-yuan Wancoxme.display: thanks for
Cristina Ganuza VallejoTableSubgroupGLM &
TableSubgroupCox allow subgroup variable with
continuous.*.display: univariate analysis with
stats::updatesvyCreateTableOneJS in example/test.svycox.displayRemove dependency with group_split function
(dplyr package)
Use survey::regTermTest for interaction p
calculation with survey::svycoxph.
CreateTableOneJS,
svyCreateTableOneJS: when with labeldata, variables other
than numeric or factor types are excluded.TableSubgroupGLM,
TableSubgroupMultiGLM: p valueTableSubgroupGLM,
TableSubgroupMultiGLM: subgroup analysis for GLM(gaussian,
logistic)showpm option with showAllLevels = F when
no strata.TableSubgroupCox: apply extend = T
option to summary.survfit
LabelepiDisplay, LabeljsTable with only
1 independent variable.
CreateTableOneJS, svyCreateTableOneJS: Add
showpm option to show normal distributed continuous
variables as Mean ± SD.LabelepiDisplay, LabeljsTable:
label error.TableSubgroupCox: error with too large
time_eventrateBugfix TableSubgroupCox: error with factor variable
including NA.
Update TableSubgroupCox: compatible with upcoming
survival pacakge update.
svycox.display: compatible with upcoming
survival pacakge update.CreateTableOneJS with 2 level
strata & psub = F.Additional bug fix: match with survival3.1-x.
class issue:
https://developer.r-project.org/Blog/public/2019/11/09/when-you-think-class.-think-again/index.html
TableSubgroupCox.TableSubgroupCox.geeglm.display.CreateTableOneJS and svyCreateTableOneJS
can get simplified table with showAllLevels = F
option.TableSubgroupMultiCox: Get sub-group analysis
table for forestplot with Cox/svycox
model.CreateTableOneJS and
svyCreateTableOneJS according to tableone
package(0.10.0).cox2.displayUpdate travis-ci
Add appveyor CI to test window environment
Add vignettes
glmshow.displaysvyCreateTableOne2, svyCreateTableOneJS,
LabelJsTable, LabelepiDisplay and
svyregress.displaycoefNA can be used in
svyregress.displaysvyglm function.
Apply testhat.
Auto-selection between Chi-square test and
Fisher’s exact test in CreateTableOneJS,
CreateTableOne2.
Table 1 for survey data: svyCreateTableOne2 and
svyCreateTableOneJS are modified functions of
svyCreateTableOne(tableone
package).
New function: coefNA
Bug fixes: Coefficients in glmshow.display,
cox2.display
cox2.displayglmshow.display,
cox2.display, geeglm.display,
coxme.displayglmshow.display: table from
glm.object.LabelepiDisplay: column name issue.svycox.display: table from svycoxph.object
in survey packagesvyregress.display: table from
svyglm.object in survey packageUpdate: cox2.display function allows
data argument.
Remove jsBasicGadget : Move to
jsmodule package.
Shiny gadget for descriptive statistics:
jsBasicGadget
Rstudio Addin of jsBasicGadget:
jsBasicAddin
geeExp, lmerExp functioncoxExp, cox2.display
functionTable from coxph.object (survival
package) - allow cluster & frailty
options: cox2.display function
Apply label information to cox2.display:
LabeljsCox function
Apply label information to geeglm.display:
LabeljsGeeglm function
geeglm.display functionApply label information to epiDisplay.object:
LabelepiDisplay function
Apply label information to lmer.display,
coxme.display: LabeljsMixed function
coxme.object (coxme
package): coxme.display functionopt.tb1 from 10 to
25.
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