View source: R/rm_compactsum.R
xvar_function | R Documentation |
Create a summary table for an individual covariate
xvar_function(
xvar,
data,
grp,
covTitle = "",
digits = 1,
digits.cat = 0,
iqr = TRUE,
all.stats = FALSE,
pvalue = TRUE,
effSize = FALSE,
show.tests = FALSE,
percentage = "col"
)
xvar |
character with the name of covariate to include in table |
data |
dataframe containing data |
grp |
character with the name of the grouping variable |
covTitle |
character with the name of the covariate (predictor) column. The default is to leave this empty for output or, for table only output to use the column name 'Covariate' |
digits |
numeric specifying the number of digits for summarizing mean data. Otherwise, can specify for individual covariates using a vector of digits where each element is named using the covariate name. If a covariate is not in the vector the default will be used for it (default is 1). See examples |
digits.cat |
numeric specifying the number of digits for the proportions when summarizing categorical data (default is 0) |
iqr |
logical indicating if you want to display the interquartile range (Q1, Q3) as opposed to (min, max) in the summary for continuous variables |
all.stats |
logical indicating if all summary statistics (Q1, Q3 + min, max on a separate line) should be displayed. Overrides iqr |
pvalue |
logical indicating if you want p-values included in the table |
effSize |
logical indicating if you want effect sizes and their 95% confidence intervals included in the table. Effect sizes calculated include Cramer's V for categorical variables, and Cohen's d, Wilcoxon r, Epsilon-squared, or Omega-squared for numeric/continuous variables |
show.tests |
logical indicating if the type of statistical test and effect size (if effSize = TRUE) used should be shown in a column beside the p-values. Ignored if pvalue = FALSE |
percentage |
choice of how percentages are presented, either column (default) or row |
A data frame is returned
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