Assessing the effect of a treatment when subjects are growing at different rates.
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The analysis of covariance is often used in the context of premeasure/postmeasure designs to compare treatment and control groups in both randomized  and nonrandomized  studies. The intent is to adjust the difference between the changes in the 2 groups for any difference which might exist at baseline, i.e., for any difference between the premeasures in the 2 groups. An important assumption underlying the use of the analysis of covariance is that the slopes of the lines for the regression of the postmeasure on the premeasure in the 2 groups are equal. In this paper we describe a program which can be used to test the hypothesis of equal slopes; and performs an alternative analysis which does not depend on this assumption. This is done in the context of comparing treatment and control groups with respect to a measurement subject to natural maturation as in . Equal slopes in this context means equal growth rates; unequal slopes implies that the 2 groups are growing at different rates. The method, known as the Johnson-Neyman procedure  is, however, more general than this, and can be used in any two-sample comparison where an alternative to the usual analysis of covariance is deemed appropriate. The procedure identifies a 'region of significance' which is especially useful in practice. This region consists of a set of values of the premeasure for which the treatment and the control groups are significantly different with respect to the postmeasure.
author list (cited authors)
Kowalski, C. J., Schneiderman, E. D., & Willis, S. M.
complete list of authors
Kowalski, CJ||Schneiderman, ED||Willis, SM