gao_cs {nparcomp}

Nonparametric multiple test procedure for all-pairs comparisons

Description

This function can be used to perform the nonparametric multiple tests for all-pairs comparisons by Gao et al. (2008). This procedure is a nonparametric equivalent of Campbell and Skillings (1981) sequential test procedure.

Usage

gao_cs(formula, data, alpha = 0.05, silent = FALSE)

Arguments

formula

A two-sided 'formula' specifying a numeric response variable and a factor with more than two levels. If the factor contains less than 3 levels, an error message will be returned.

data

A dataframe containing the variables specified in formula.

alpha

The significance level (by default = 0.05).

silent

A logical indicating more informations should be print on screen.

Value

Info

Samples and sizes with estimated relative effects and variance estimators.

Single.Analysis

Comp: Distributions being compared, Effect: Estimated effect, Statistic: Teststatistic, DF: Degree of Freedom, P.Raw: Raw p-Value, P.Bonf: Bonferroni adjusted p-Values, P.Holm: Holm adjusted p-Value.

CS.Analysis

Comp: Distributions being compared, Effect: Estimated effect, Statistic: Teststatistic, DF: Degree of Freedom, Quantiles: quantile, Adj. P: adjusted p-Value, Alpha: Significance level alpha, Rejected: A logical indicating rejected hypotheses, Layer: Layer of the stepwise analysis.

Note

The generalized Campbell and Skillings' analysis is performed in the CS.Analysis output. The adjusted quantiles and p-Values are reported. Due to the non-monotonicity of the adjusted quantiles, all results are checked for non-logical relations.

Author(s)

Frank Konietschke

References

Gao, X. et al. (2008). Nonparametric Multiple Comparison Procedures for Unbalanced One-Way Factorial Designs. JSPI 138, 2574 - 2591.

Konietschke, F., Placzek, M., Schaarschmidt, S., Hothorn, L.A. (2014). nparcomp: An R Software Package for Nonparametric Multiple Comparisons and Simultaneous Confidence Intervals. Journal of Statistical Software, 61(10), 1-17.

See Also

For nonparametric many-to-one comparison see gao.

Examples

## Not run: 
data(reaction)

gao_cs(Time ~Group, data=reaction,alpha=0.05)

## End(Not run)