- data
dataframe containing data
- covs
character vector with the names of columns to include in table
- maincov
covariate to stratify table by
- id
covariates to nest summary by
- caption
character containing table caption (default is no caption)
- tableOnly
Logical, if TRUE then a dataframe is returned, otherwise a
formatted printed object is returned (default).
- covTitle
character with the names 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
number of digits for summarizing mean data
- digits.cat
number of digits for the proportions when summarizing
categorical data (default: 0)
- nicenames
boolean indicating if you want to replace . and _ in strings
with a space
- IQR
boolean indicating if you want to display the inter quantile range
(Q1,Q3) as opposed to (min,max) in the summary for continuous variables
- all.stats
boolean indicating if all summary statistics (Q1,Q3 +
min,max on a separate line) should be displayed. Overrides IQR.
- pvalue
boolean indicating if you want p-values included in the table
- effSize
boolean indicating if you want effect sizes included in the
table. Can only be obtained if pvalue is also requested.
- p.adjust
p-adjustments to be performed
- unformattedp
boolean indicating if you would like the p-value to be
returned unformatted (ie not rounded or prefixed with '<'). Best used with
tableOnly = T and outTable function.
- show.tests
boolean indicating if the type of statistical used should
be shown in a column beside the p-values. Ignored if pvalue=FALSE.
- just.nested.pvalue
boolean indicating if the just the nested p-value
should be shown in a column, and not unnested p-value, unnested statistical
tests and effect size. Overrides effSize and show.tests arguments.
- nCores
number of cores to use for parallel processing if calculating
the nested p-value (if provided).
- nested.test
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.
- nsim
specifies number of simulations to use for calculating nested p-value
with parametric bootstrap method used for nested.test (default: 1000).
- testcont
test of choice for continuous variables,one of
rank-sum (default) or ANOVA
- testcat
test of choice for categorical variables,one of
Chi-squared (default) or Fisher
- full
boolean indicating if you want the full sample included in the
table, ignored if maincov is NULL
- include_missing
Option to include NA values of maincov. NAs will not
be included in statistical tests
- percentage
choice of how percentages are presented, one of
column (default) or row
- dropLevels
logical, indicating if empty factor levels be dropped from
the output, default is TRUE.
- excludeLevels
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 (ie not missing, but not
presented). Ignored if pvalue=FALSE.
- numobs
named list overriding the number of people you expect to have
the covariate
- markup
boolean indicating if you want latex markup
- sanitize
boolean indicating if you want to sanitize all strings to not
break LaTeX
- chunk_label
only used if output is to Word to allow cross-referencing