summarydata: Summary of Continuous Variables

In sbalci/ClinicoPathDescriptives: Descriptive Analysis Tools for Clinicopathological Research

Summary of Continuous Variables

Description

This module generates descriptive statistics for continuous variables. It provides both a textual summary and a visually appealing summary table. Optionally, you can enable distribution diagnostics to examine normality, skewness, and kurtosis.

Usage

summarydata(
  data,
  vars,
  date_vars = NULL,
  distr = FALSE,
  summary_format = "standard",
  grvar = NULL,
  pivot_layout = "clinical",
  include_confidence = TRUE,
  advanced_metrics = FALSE,
  pivot_export = FALSE,
  summarytools_graphs = TRUE,
  summarytools_round_digits = 2
)

Arguments

data	The data as a data frame.
vars	a string naming the variables from data that contains the continuous values used for the report
date_vars	Variables containing date/time data to be analyzed with date-specific statistics (similar to sumvar's dist_date function)
distr	If TRUE, additional distribution diagnostics (Shapiro-Wilk test, skewness, and kurtosis) will be computed and explained.
summary_format	Choose the format for summary statistics display. New summarytools options provide publication-ready automated EDA summaries with embedded visualizations.
grvar	Optional grouping variable to stratify the summary statistics by categories.
pivot_layout	Layout style for pivottabler enhanced summaries.
include_confidence	Include confidence intervals in pivot summary tables.
advanced_metrics	Include advanced metrics like IQR, MAD, and robust statistics.
pivot_export	Enable enhanced export capabilities for pivot tables.
summarytools_graphs	Include histograms and bar charts in summarytools dfSummary output.
summarytools_round_digits	Number of decimal places for summarytools output.

Value

A results object containing:

results$todo					a html
results$text					a html
results$text1					a html
results$pivot_summary					a html
results$pivot_export_info					a html

Examples

# Example:
# 1. Load your data frame.
# 2. Select one or more continuous variables.
# 3. (Optional) Enable Distribution Diagnostics to view additional tests.
# 4. Run the summarydata module to see descriptive statistics and distribution characteristics.

sbalci/ClinicoPathDescriptives documentation built on July 4, 2025, 5:25 p.m.