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Min and max scorings for two sample partially ordered categorical data.

Authors
Sampson-AR; Singh-H
Source
J Stat Plann Inference 2002 Sep; 107(1-2):219-236
NIOSHTIC No.
20022954
Abstract
For certain types of designed experiments the outcome variables are ordinal categorical variables. Such experiments are typical in many behavioral science and social science settings, as well as in certain types of clinical trials. The representation, analysis and summarization of the results of such experiments can be difficult and complex. We present one analytical approach to these settings that uses scalings for a simpler presentation of the results. The resulting scalings can be viewed as a technique for reducing the complexity of the multivariate ordinal response data and providing insightful data summaries. Utilizing some of the results for designed experiments with univariate ordinal responses, we introduce new techniques to handle responses taking values in a partially ordered set. These latter results are applied to scaling multivariate ordinal data. Several data sets are analyzed using this new approach.
Keywords
Behavioral-testing; Behavioral-tests; Clinical-tests; Clinical-techniques; Analytical-methods; Statistical-analysis
CODEN
JSPIDN
Publication Date
20020901
Document Type
Journal Article
Email Address
asampson@stat.pitt.edu
Fiscal Year
2002
NTIS Accession No.
NTIS Price
Issue of Publication
1-2
ISSN
0378-3758
NIOSH Division
HELD
Source Name
Journal of Statistical Planning and Inference
State
PA; WV
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