Overall.And.Stratified: Creating Overall and Stratified Tables

In UKBiostatCIRCL/UK-Biostat-CIRCL: UKBiostatCIRCL: A package for the common functions of the Biostat CIRCL at the University of Kentucky

Creating Overall and Stratified Tables

Description

This function is designed to create a summary table using lists of continuous and categorical variables (specified). Overall or stratified tables can be constructed or if a stratification variable is included. Additionally, p-values are output using either ANOVA (for continuous variables) or Chi-square (for categorical variables) tests.

Usage

Overall.And.Stratified(
  dataset = dat,
  strata.variable = NULL,
  variables,
  variable.labels = NULL,
  factor.variables = NULL,
  factors_reported.categorical.analyzed.ordinal = NULL,
  exact.variables = NULL,
  exact.variables_detect.and.add.to.list = TRUE,
  categorical.variables_force.exclusion.from.exact.analysis = NULL,
  categorical.variables_report.all.levels = FALSE,
  non.normal.variables = NULL,
  all.patients.row.name = "All Patients",
  descriptors_include = TRUE,
  descriptor_categorical = ", N (%)",
  descriptor_continuous_default = ", Mean (SD)",
  descriptor_continuous_nonnormal = ", Median [Q1,Q3]",
  digits_pvalue = 3,
  digits_categorical = 1,
  digits_continuous = 2,
  missing.data_include.as.list = TRUE,
  missing.data_include.as.separate.table = TRUE,
  missing.data_add.to.table = FALSE,
  missing.data_row.label = "Missing Obs.",
  missing.data_value.prefix = "N="
)

Arguments

dataset	A data.frame object containing, at minimum, all of the variables contained in the table.
strata.variable	= the name of the categorical/pordinal variable that you wish to stratify on. May also be left as NULL for an overall table.
variables	= a vector of the variable names you wish to include as rows in the table.
variable.labels	= an optional vector of labels that will be displayed instead of the variable name, Must be the same length as the variables vector.
factor.variables	= an optional vector of variable names that are numeric but should be coereced into categorical.
factors_reported.categorical.analyzed.ordinal	= an optional vector of variable names where frequencies are reported but the variables are analyzed as ordinal.
exact.variables	= an optional vector of variable names where Fisher's exact should be used.
exact.variables_detect.and.add.to.list	= TRUE/FALSE whether or not to run a chi-square test on the categorical variables and if a warning is produced run Fisher's exact.
categorical.variables_force.exclusion.from.exact.analysis	= an optional vector of variable names that will be coerced into the chi-square test.
categorical.variables_report.all.levels	= if TRUE, then both levels of two-level categorical variables will be reported
non.normal.variables	= an optional vector of variable names where a non-parametric test will be used instead of a t-test/one-way ANOVA.
all.patients.row.name	= a character string that will be displayed in the top row of the table which typically contrains the strata-specific frequencies.
descriptors_include	= TRUE/FALSE to include the statistic description after the variable label in the rows of the table.
descriptor_categorical	= a character string of the descriptor to include after categorical variables.
descriptor_continuous_default	= a character string of the descriptor to include after continuous variables.
descriptor_continuous_nonnormal	= a character string of the descriptor to include after non-normal continuous variables.
digits_pvalue	= a numeric value for the number of digits to report for p-values.
digits_categorical	= a numeric value for the number of digits to report for percentages.
digits_continuous	= a numberic value for the number of digits to report for numeric values.
missing.data_include.as.list	= TRUE/FALSE for whether or not to generate a character string to describe the variables with missing data.
missing.data_include.as.separate.table	= TRUE/FALSE for whether or not to generate a separate table summarizing the variables with missing data.
missing.data_add.to.table	= TRUE/FALSE whether or not to add an additional row below a variable for the purposes of reporting missing values.
missing.data_row.label	= a character string for the row label that will be used for missing data rows
missing.data_value.prefix	= a character string for the pre-fix to include before the missing data frequencies in the body of the table.

UKBiostatCIRCL/UK-Biostat-CIRCL documentation built on June 30, 2022, 4:42 a.m.