Nested version of reportRmd covsum()
covsum_nested(
data,
covs,
maincov = NULL,
id = NULL,
digits = 1,
numobs = NULL,
markup = TRUE,
sanitize = TRUE,
nicenames = FALSE,
IQR = FALSE,
all.stats = FALSE,
pvalue = TRUE,
effSize = TRUE,
show.tests = TRUE,
nCores = NULL,
nested.test = NULL,
nsim = NULL,
excludeLevels = NULL,
dropLevels = TRUE,
full = TRUE,
digits.cat = 0,
testcont = c("rank-sum test", "ANOVA"),
testcat = c("Chi-squared", "Fisher"),
include_missing = FALSE,
percentage = c("column", "row")
)dataframe containing data
character vector with the names of columns to include in table
covariate to stratify table by
covariates to nest summary by
number of digits for summarizing mean data, does not affect p-values
named list overriding the number of people you expect to have the covariate
boolean indicating if you want latex markup
boolean indicating if you want to sanitize all strings to not break LaTeX
boolean indicating if you want to replace . and _ in strings with a space
boolean indicating if you want to display the inter quantile range (Q1,Q3) as opposed to (min,max) in the summary for continuous variables
boolean indicating if all summary statistics (Q1,Q3 + min,max on a separate line) should be displayed. Overrides IQR.
boolean indicating if you want p-values included in the table
boolean indicating if you want effect sizes included in the table. Can only be obtained if pvalue is also requested.
boolean indicating if the type of statistical used should be shown in a column beside the p-values. Ignored if pvalue=FALSE.
if > 1, specifies number of cores to use for parallel processing for calculating the nested p-value (default: 1).
specifies test used for calculating nested p-value from afex::mixed function. Either parametric bootstrap method or likelihood ratio test method (default: "LRT"). Parametric bootstrap takes longer.
specifies number of simulations to use for calculating nested p-value with parametric bootstrap method used for nested.test (default: 1000).
a named list of covariate levels to exclude from statistical tests in the form list(varname =c('level1','level2')). These levels will be excluded from association tests, but not the table. This can be useful for levels where there is a logical skip (i.e. not missing, but not presented). Ignored if pvalue=FALSE.
logical, indicating if empty factor levels be dropped from the output, default is TRUE.
boolean indicating if you want the full sample included in the table, ignored if maincov is NULL
number of digits for the proportions when summarizing categorical data (default: 0)
test of choice for continuous variables,one of rank-sum (default) or ANOVA
test of choice for categorical variables,one of Chi-squared (default) or Fisher
Option to include NA values of maincov. NAs will not be included in statistical tests
choice of how percentages are presented, one of column (default) or row