STEPWISE MULTIPLE COMPARISON PROCEDURES FOR NORMAL VARIANCES

Pairwise multiple comparisons: a model comparison approach versus stepwise procedures.

Researchers in the behavioural sciences have been presented with a host of pairwise multiple comparison procedures that attempt to obtain an optimal combination of Type I error control, power, and ease of application. However, these procedures share one important limitation: intransitive decisions. Moreover, they can be characterized as a piecemeal approach to the problem rather than a holistic...

Testing equality of variances for multiple univariate normal populations

A Multiple Comparison Procedure for Populations with Unequal Variances

This article investigates an exact method that extends Dunnett’s method on the multiple comparisons with a control (MCC) to the case of unequal error variances when the ratios of population variances of k new treatments to that of the control group are known from previous experience. The advantages of the proposed method is illustrated through an example. The simulation results show that the ty...

Multiple Comparison Procedures

1. Introduction Analysis of variance is used to test for the real treatment differences. When the null hypothesis that all the treatment means are equal is not rejected, it may seem that no further questions need to be asked. However, in some experimental situations, it may be an oversimplification of the problem. For example, consider an experiment in rice weed control with 15 treatments viz. ...

Multiple-Comparison Procedures for Steady-State Simulations

Suppose that there are k ≥ 2 different systems (i.e., stochastic processes), where each system has an unknown steady-state mean performance and unknown asymptotic variance. We allow for the asymptotic variances to be unequal and for the distributions of the k systems to be different. We consider the problem of running independent, single-stage simulations to make multiple comparisons of the ste...