ASSESSING THE EFFECT OF A TREATMENT WHEN SUBJECTS ARE GROWING AT DIFFERENT RATES

The analysis of covariance is often used in the context of premeasure/ postmeasure designs to compare treatment and control groups in both ra ndomized [1] and nonrandomized [2] studies. The intent is to adjust th e difference between the changes in the 2 groups for any difference wh ich might exist at baseline, i.e., for any difference between the prem easures in the 2 groups. An important assumption underlying the use of the analysis of covariance is that the slopes of the lines for the re gression of the postmeasure on the premeasure in the 2 groups are equa l. In this paper we describe a program which can be used to test the h ypothesis of equal slopes; and performs an alternative analysis which does not depend on this assumption. This is done in the context of com paring treatment and control groups with respect to a measurement subj ect to natural maturation as in [3]. Equal slopes in this context mean s equal growth rates; unequal slopes implies that the 2 groups are gro wing at different rates. The method, known as the Johnson-Neyman proce dure [4] is, however, more general than this, and can be used in any t wo-sample comparison where an alternative to the usual analysis of cov ariance is deemed appropriate. The procedure identifies a 'region of s ignificance' which is especially useful in practice. This region consi sts of a set of values of the premeasure for which the treatment and t he control groups are significantly different with respect to the post measure.