Using Fixed and Relative Optimal Discriminant Thresholds in Randomized Blocks (Matched-Pairs) Designs

Paul R. Yarnold & Ariel Linden

Optimal Data Analysis, LLC & Linden Consulting Group, LLC

Optimal discriminant analysis (ODA) is often used to compare values of one (or more) attributes between two (or more) groups of observations with respect to a fixed discriminant threshold that maximizes accuracy normed against chance for the sample. However, a recent study using a matched-pairs design found that using a relative discriminant threshold to assess an (exploratory or confirmatory) a priori hypothesis separately for each pair of observations can identify inter-group differences which otherwise are too subtle to be identified by using fixed thresholds. The present investigation replicates the finding regarding efficacy of relative thresholds for matched-pairs designs, this time for a randomized blocks design consisting of two patient groups (one group assigned to take an antidepressant drug, the other group assigned to take a placebo) between which a numerical measure of depression was compared. Several recommendations are made concerning use of improved modern optimal statistical alternatives for this class of experimental design.

View journal article