Computing min and max scorings for two-sample ordinal data
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Authors
Whitaker, Lyn R.
Whitaker, Michael D.
Subjects
SAS software
Ordinal Data
Two-sample
Ordinal Data
Two-sample
Advisors
Date of Issue
1996-01
Date
1996-01
Publisher
Monterey, California. Naval Postgraduate School
Language
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.
Type
Technical Report
Description
Series/Report No
Department
Operations Research
Identifiers
NPS Report Number
NPS-OR-96-002
Sponsors
Funder
Format
15 p. ; 28 cm.