THE SYMMETRY OF SYMPTOM PATTERNS IN PRE-POST TREATMENT DESIGNS

This article proposes a new nonparametric method for statistical evalu ation of clinical pre-post treatment designs. In clinical research, mo dels of marginal symmetry typically are estimated from log-linear mode ls of axial and quasi-symmetry. As such, they provide overall goodness -of-fit information concerning change in probabilities of categories o f one variable that was observed twice. This paper proposes the follow ing three extensions: (1) using models of marginal symmetry for change s in patterns of two or more variables, and (2) following up global ma rginal symmetry tests using Lehmacher's sign tests. (3) To protect the experiment-wise alpha, a modified Bonferroni-Holm procedure is propos ed. The new approach allows researchers to make statements about treat ment effects at the level of single symptoms. Examples illustrate appl ication of all three symmetry models and the follow-up test using data from pharmaco-psychiatry. The discussion relates Lehmacher's tests to two-sample Configural Frequency Analysis of multi-discrimination type s. Strategies of statistical significance testing are presented and th e importance of the proposed methodological approach for psychiatric r esearch is discussed.