DemographicTable: Create Demographic Table

Description

Create a demographic table with simple summary statistics, with optional comparison(s) over one or more groups.

Usage

DemographicTable(
  data,
  data.name = substitute(data),
  groups = NULL,
  exclude = NULL,
  exclude_rx,
  include,
  include_rx,
  robust = TRUE,
  overall = TRUE,
  compare = TRUE,
  pairwise = 3L,
  ...
)

Value

Function DemographicTable() returns an object of S3 class 'DemographicTable', which is a listof

'sumtab' elements.

Arguments

data: a data.frame
data.name: character scalar, or the argument call of data. A user-friendly name of the input data.
groups: character scalar or vector, the name(s) of sub-group(s) for which the summary statistics are provided. Default NULL indicating no sub-groups.
exclude: character vector, the name(s) of variable(s) to be excluded. Default NULL indicating no variable are excluded.
exclude_rx: (optional) regex, pattern of the names of the variable(s) to be excluded.
include: character vector, the name(s) of variable(s) to be included. Default names(data) indicating all variables are included.
include_rx: (optional) regex, pattern of the names of the variable(s) to be included.
robust: logical scalar. If TRUE (default), use non-parametric methods for non-normally distributed numeric variables.
overall: logical scalar. If TRUE (default), a column of overall summary statistics will be provided.
compare: logical scalar. If TRUE (default), comparisons between group(s) will be made.
pairwise: integer scalar, minimum number of groups where pairwise comparisons need to be performed. Default 3L.
...: additional parameters, currently not in use

Details

A demographic table with simple summary statistics, with optional comparison(s) over one or more groups, is created.

numeric variables are summarized in means, standard deviations, medians, inter-quartile-ranges (IQR), skewness, \(p\)-value of Shapiro-Wilk normality test and ranges. If group is specified, they are compared using two-sample t.test, wilcox.test (Wilcoxon / Mann-Whitney), one-way aov (ANOVA) and/or kruskal.test (Kruskal-Wallis).

logical and factor variables are summarized in counts and percentages. If group is specified, they are compared using prop.test (chi-squared) and/or fisher.test (Fisher's exact).