Empirical .05 and .01 rates of Type I error were compared for the Tukey and Scheffé multiple comparison techniques. The experimentwise error rate was defined over five sets of the all possible 25 differences of averages contrasts. The robustness of the Tukey and Scheffé statistics was not only related to the type of assumption violation, but also to the sets containing different numbers of contrasts. The Tukey method could be judged as robust a statistic as the Scheffé method.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline
Behavioral science researchers often wish to compare the means of several treatment conditions on a ...
<p>It has been more than half a century since Tukey first introduced graphical displays that relate ...
For multiple comparisons in analysis of variance, the practitioners' handbooks generally advocate st...
This paper describes a Pascal microcomputer program that com-putes all painvise comparisons of means...
Type I error control accuracy of four commonly used pairwise mean comparison procedures, conducted a...
Using Tukey–Kramer versus the ANOVA F-test as the omnibus test of the Hayter–Fisher procedure for co...
Several authors have compared multiple comparison procedures under the assumption of normality and w...
Abstract In statistics, multiple comparison or multiple testing problems arise when there are a set ...
Multiple comparison problems arise when a set of inferences are considered simultaneously. When a se...
J. Barnette and J. McLean (1996) proposed a method of controlling Type I error in pairwise multiple ...
We show that the one-way ANOVA and Tukey–Kramer (TK) tests agree on any sample with two groups. This...
Investigating differences between means of more than two groups or experimental conditions is a rout...
The present study extends the previous one-way ANOVA multiple-comparison findings of Meyers and Bere...
The author examined how, in the context of experimental design, one might become aware of the Behren...
Standard approaches for analyzing the difference in two means, where partially overlapping samples a...
Behavioral science researchers often wish to compare the means of several treatment conditions on a ...
<p>It has been more than half a century since Tukey first introduced graphical displays that relate ...
For multiple comparisons in analysis of variance, the practitioners' handbooks generally advocate st...
This paper describes a Pascal microcomputer program that com-putes all painvise comparisons of means...
Type I error control accuracy of four commonly used pairwise mean comparison procedures, conducted a...
Using Tukey–Kramer versus the ANOVA F-test as the omnibus test of the Hayter–Fisher procedure for co...
Several authors have compared multiple comparison procedures under the assumption of normality and w...
Abstract In statistics, multiple comparison or multiple testing problems arise when there are a set ...
Multiple comparison problems arise when a set of inferences are considered simultaneously. When a se...
J. Barnette and J. McLean (1996) proposed a method of controlling Type I error in pairwise multiple ...
We show that the one-way ANOVA and Tukey–Kramer (TK) tests agree on any sample with two groups. This...
Investigating differences between means of more than two groups or experimental conditions is a rout...
The present study extends the previous one-way ANOVA multiple-comparison findings of Meyers and Bere...
The author examined how, in the context of experimental design, one might become aware of the Behren...
Standard approaches for analyzing the difference in two means, where partially overlapping samples a...
Behavioral science researchers often wish to compare the means of several treatment conditions on a ...
<p>It has been more than half a century since Tukey first introduced graphical displays that relate ...
For multiple comparisons in analysis of variance, the practitioners' handbooks generally advocate st...