Computing Min and Max Scorings for Two-Sample Ordinal Data.
Abstract
Ordinal response variables often occur in practice. For example, in clinical trials a subject's response to a drug regime might be categorized as negative, none, fair, or good. There are several common approaches to analyzing two-sample ordinal response data. These procedures applied to the same data can lead to contradictory conclusions. In an attempt to reconcile contradictory results and provide guidance to the practitioner, Kimledorf, Sampson and Whitaker (1992) propose an alternative approach. They find the scores which when assigned to the levels of the ordinal response variable maximize a two-sample test statistic and the scores that minimize that same statistic. Since many of the two-sample statistics are related by monotonic transformations, these extreme scores are in fact extreme scores for several test statistics. Both minimized and maximized test statistics falling into the rejection region clearly indicate a difference between the two populations or treatments. On the other hand if neither of the two extreme statistics fall in the rejection region then no matter what scores are used there will be no significant difference in the two populations. In this paper we review the KsW procedure and its implementation in SAS software.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1996
- Accession Number
- ADA304769
Entities
People
- Jyn R. Whitaker
- Michael D. Whitaker
Organizations
- Naval Postgraduate School