McSweeny_Porter: McSweeny and Porter Method for Nonparametric ANCOVA

In npANCOVA: Nonparametric ANCOVA Methods

McSweeny and Porter Method for Nonparametric ANCOVA

Description

Performs rank-based ANCOVA with and without an interaction term between the covariates and the group.

Usage

McSweeny_Porter(data, formula)

Arguments

data	A data frame containing the variables specified in the formula.
formula	An object of class "formula": a symbolic description of the model to be fitted. The structure should be 'response ~ covariate1 + ... + group'.

Value

A list containing the following components:

regression_equation_covariate

Summary of the model with only covariates.

regression_equation_covariate_group

Summary of the model with covariates and group main effects.

group_effect

The result of an ANOVA test for group effect.

interaction_effect

The result of an ANOVA test for interaction effect between group and covariate variables.

regression_equation_interaction

Summary of the model including the interaction term.

data

The original data frame with added columns for ranks.

References

McSweeney M, Porter AJOp. Small sample properties of nonparametric index of response and rank analysis of covariance. 1971;16.

Olejnik SF, Algina JJER. A review of nonparametric alternatives to analysis of covariance. 1985;9(1):51-83.

Examples

# 1. Create a sample data frame
data <- data.frame(
  group = c(1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3),
  response = c(16, 60, 82, 126, 137, 44, 67, 87, 100, 142, 17, 28, 105, 149, 160),
  covariate1 = c(26, 10, 42, 49, 55, 21, 28, 5, 12, 58, 1, 19, 41, 48, 35),
  covariate2 = c(12, 21, 24, 29, 34, 17, 2, 40, 38, 36, 8, 1, 9, 28, 16)
)

# 2. Run the McSweeny and Porter method
results <- McSweeny_Porter(
  formula = response ~ covariate1 + covariate2 + group,
  data = data
)

# 3. View the results
print(results)
print(results$group_effect)
print(results$interaction_effect)

npANCOVA documentation built on Nov. 9, 2025, 5:06 p.m.