covsum_nested {BiostatsUHNplus}

Nested version of reportRmd covsum()

Description

Nested version of reportRmd covsum()

Usage

covsum_nested(
  data,
  covs,
  maincov = NULL,
  id = NULL,
  digits = 1,
  numobs = NULL,
  markup = TRUE,
  sanitize = TRUE,
  nicenames = TRUE,
  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")
)

Arguments

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

digits

number of digits for summarizing mean data, does not affect p-values

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

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.

show.tests

boolean indicating if the type of statistical used should be shown in a column beside the p-values. Ignored if pvalue=FALSE.

nCores

if > 1, specifies number of cores to use for parallel processing for calculating the nested p-value (default: 1).

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).

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 (i.e. not missing, but not presented). Ignored if pvalue=FALSE.

dropLevels

logical, indicating if empty factor levels be dropped from the output, default is TRUE.

full

boolean indicating if you want the full sample included in the table, ignored if maincov is NULL

digits.cat

number of digits for the proportions when summarizing categorical data (default: 0)

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

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

See Also

fisher.test,chisq.test, wilcox.test,kruskal.test, anova and mixed