DTK.test {DTK} R Documentation

## Dunnett's Modified Tukey-Kramer Pairwise Multiple Comparison Test

### Description

Conducts a pairwise multiple comparison test (using the C procedure) for mean differences with unequal sample sizes and no assumption of equal population variances.

### Usage

DTK.test(x = "data vector", f = "factor vector", a = "alpha level")


### Arguments

 x Numeric data vector. f Factored level vector. a Alpha, significance level. DEFAULT=0.05

### Details

Input data as vectors.

### Value

 [[1]] "a" or the alpha significance level [[2]] Matrix containing the pair-waise comparisons as row names and the pairwise mean differences and lower and upper confidence interval values in columns, respectively

### Note

In the case of equal sample sizes and equal population variances, Dunnett's test (the T3 Procedure) produces slightly wider (i.e. more conservative) confidence intervals than the Tukey-Kramer procedure. This is because of differences in the degrees of freedom used for determining the Studentized Range values. In cases where variances are unequal, however, the Tukey-Kramer test, which uses the pooled variance, will spread variance across levels and produce misleading results.

### Author(s)

Matthew K. Lau, Department of Biological Sciences, Northern Arizona University, AZ

### References

Dunnett,C.W. (1980) Pairwise Multiple Comparisons in the Unequal Variance Case. Journal of the American Statistical Association. 75 (372): 796-800.

DTK.plot, gl.unequal, TK.test, TukeyHSD, qtukey
x=c(rnorm(25,5,2),rnorm(30,5,5),rnorm(35,15,5))