Description Usage Arguments Value Note Author(s) References See Also Examples
This function can be used to perform the nonparametric multiple tests for many-to-one comparisons by Gao et al. (2008). The multiple level is strongly controlled by the Hochberg-adjustment.
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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). |
control |
Character string defining the control group in Dunnett comparisons. By default it is the first group by lexicographical ordering |
silent |
A logical indicating more informations should be print on screen. |
Info |
Samples and sizes with estimated relative effects and variance estimators. |
Analysis |
Comparison: Distributions being compared, Estimator: Estimated effect, df: Degree of Freedom, Statistic: Teststatistic, P.Raw: Raw p-Value P.Hochberg: Adjusted p-Value by the Hochberg adjustment, Rejected: A logical indicating rejected hypotheses, P.Bonf: Bonferroni adjusted p-Values, P.Holm: Holm adjusted p-Value. |
The procedure can only be used to test hypotheses in terms of the distribution functions.
Frank Konietschke
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.
For nonparametric all-pairs comparison see gao_cs
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