f_chisq_test: Chi-squared Test with Post-hoc Analysis

In rfriend: Provides Batch Functions and Visualisation for Basic Statistical Procedures

Chi-squared Test with Post-hoc Analysis

Description

Performs a chi-squared test chisq.test, then automatically conducts post-hoc analysis if the test is significant. The function provides adjusted p-values for each cell in the contingency table using a specified correction method.

Usage

f_chisq_test(
  x,
  y,
  p = NULL,
  method = "bonferroni",
  digits = 3,
  alpha = 0.05,
  force_posthoc = FALSE,
  ...
)

Arguments

x	A numeric vector (or factor), or a contingency table in matrix or table form. If a data frame is entered the function will try to convert it to a table.
y	A numeric vector; ignored if x is a matrix, table or data.frame. If x is a factor, y should be a factor of the same length.
p	A vector of probabilities of the same length as x. Default is NULL. An error is given if any entry of p is negative.
method	Character string specifying the adjustment method for p-values. Default is "bonferroni". Other options include "holm", "hochberg", "hommel", "BH", "BY", "fdr", and "none".
digits	Integer specifying the number of decimal places for rounding. Default is 3.
alpha	Numeric threshold for significance. Default is 0.05.
force_posthoc	Logical indicating whether to perform post-hoc tests even if the chi-squared test is not significant. Default is FALSE.
...	Additional arguments passed to chisq.test.

Details

The function first performs a chi-squared test using chisq.test. If the test is significant (p < alpha) or if force_posthoc = TRUE, it conducts post-hoc analysis by examining the standardized residuals. The p-values for these residuals are adjusted using the specified method to control for multiple comparisons.

If the input is a data frame, the function attempts to convert it to a table and displays the resulting table for verification.

Value

An object of class f_chisq_test containing:

• chisq_test_output: The output from chisq.test.

• adjusted_p_values: Matrix of adjusted p-values (for table/matrix input).

• observed_vs_adj_p_value: Interleaved table of observed values and adjusted p-values.

• stdres_vs_adj_p_value: Interleaved table of standardized residuals and adjusted p-values.

• adj_p_values: Vector of adjusted p-values (for vector input).

• posthoc_output_table: Data frame with observed values, expected values, standardized residuals, and adjusted p-values (for vector input).

Author(s)

Sander H. van Delden [e-mail]

References

This function implements a post-hoc analysis for chi-squared tests inspired by the methodology in:

Beasley, T. M., & Schumacker, R. E. (1995). Multiple Regression Approach to Analyzing Contingency Tables: Post Hoc and Planned Comparison Procedures. The Journal of Experimental Education, 64(1), 79-93.

The implementation draws inspiration from the 'chisq.posthoc.test' package by Daniel Ebbert.

Examples

# Chi.square on independence: Association between two variables.
# Create a contingency table.
my_table <- as.table(rbind(c(100, 150, 50), c(120, 90, 40)))
dimnames(my_table) <- list(Gender = c("Male", "Female"),
                           Response = c("Agree", "Neutral", "Disagree"))

# Perform chi-squared test with post-hoc analysis.
f_chisq_test(my_table)

# Use a different adjustment method.
f_chisq_test(my_table, method = "holm")

# Other forms still work like Goodness-of-Fit: Match to theoretical distribution.
# Observed frequencies of rolling with a die 1 - 6.
observed <- c(2, 2, 10, 20, 15, 11)

# Expected probabilities under a fair die.
expected_probs <- rep(1/6, 6)

# Chi-Square Goodness-of-Fit Test.
f_chisq_test(x = observed, p = expected_probs)

rfriend documentation built on Aug. 8, 2025, 7:33 p.m.