steel: Steel-type multiple contrast tests

In rankFD: Rank-Based Tests for General Factorial Designs

Steel-type multiple contrast tests

Description

The function implements purely nonparametric Steel-type multiple contrast tests for either making many-to-one (Dunnett-type) or all pairwise (Tukey-type) comparisons. Null hypotheses are formulated in terms of the distribution functions.

Usage

steel(
  formula,
  data,
  control = NULL,
  alternative = c("two.sided", "less", "greater"),
  info = TRUE,
  correlation = TRUE
)

Arguments

formula	A model formula object. The left hand side contains the response variable and the right hand side contains the factor variable of interest.
data	A data.frame, list or environment containing the variables in formula. The default option is NULL.
control	Specification of the control group for making many-to-one-comparisons. If NULL, all-pairwise comparisons are performed.
alternative	Specification of the direction of the alternative. Default is two-sided.
info	Logical. If TRUE, additional output information and explanation is printed to the console.
correlation	Logical. If TRUE, the correlation matrix is printed.

Details

The steel() function calculates the Steel-type tests as explained by Munzel, U., Hothorn, L. A. (2001). A unified approach to simultaneous rank test procedures in the unbalanced one-way layout. Biometrical Journal: Journal of Mathematical Methods in Biosciences, 43(5), 553-569.

Value

A list containing the following components:

Data.Info	Groups and sample sizes of the data
Analysis	Data frame containing the test results (comparison, relative effect estimator, standard error, test statistic and p-value.)
Correlation	Estimated correlation matrix

References

Brunner, E., Bathke, A.C., Konietschke, F. Rank and Pseudo-Rank Procedures for Independent Observations in Factorial Designs. Springer International Publishing, 2018.

Munzel, U., Hothorn, L. A. (2001). A unified approach to simultaneous rank test procedures in the unbalanced one-way layout. Biometrical Journal: Journal of Mathematical Methods in Biosciences, 43(5), 553-569.

Konietschke, F., Hothorn, L. A., Brunner, E. (2012). Rank-based multiple test procedures and simultaneous confidence intervals. Electronic Journal of Statistics, 6, 738-759.

Examples

data(Muco)
model.oneway <- steel(HalfTime ~ Disease, data = Muco,info=TRUE,correlation=TRUE)

rankFD documentation built on March 23, 2022, 5:08 p.m.