npANCOVA (version 0.1.1)

McSweeny_Porter: 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)

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.

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`.

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)