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NCJ Number: 97520 Add to Shopping cart Find in a Library
Title: Predictive Attribute Analysis With Validation Extensions User's Guide for the PAAVE Computer Program
Author(s): N F Walker
Corporate Author: New York State
Division of Criminal Justice Services
Office of Policy Analysis Research and Statistical Service
Date Published: 1985
Page Count: 163
Sponsoring Agency: National Institute of Justice/
Rockville, MD 20849
NCJRS Photocopy Services
Rockville, MD 20849-6000
New York State
Albany, NY 12203
Sale Source: National Institute of Justice/
NCJRS paper reproduction
Box 6000, Dept F
Rockville, MD 20849
United States of America

NCJRS Photocopy Services
Box 6000
Rockville, MD 20849-6000
United States of America
Document: PDF
Language: English
Country: United States of America
Annotation: This user's guide defines predictive attribute analysis (PAA), a technique for sequentially dividing groups on the basis of attributes of those groups that effectively predict a criterion; various functions and capabilities of the mainframe FORTRAN computer program for PAA are described.
Abstract: Methodological issues which have arisen about the use of the PAA as a general purpose prediction method are considered, and relate to PAA's reliability and validity. The predictive attribute analysis with validation extensions (PAAVE) computer program, an implementation of the procedure for conducting a PAA, is addressed. Attention is focused on the PAA algorithm, parameter specification, data input and manipulation, dichotimization, contingency table construction, statistical coefficients, and branch termination criteria. Additionally, analysis output and bootstrap resampling are addressed; consideration is given to processing specifications and options. Program dimensions and limitations are analyzed, and the possibility of determining up to 64 terminal subgroups, 5 PPA levels, is reported. The PAAVE program's capability of using up to seven online files for various input/output functions is noted, and the creation, initialization, and storage of these files is explained. The general use of the program is described in the context of program installation, program compilation and object-code generation, online file considerations, and program execution and output redirection. Finally, two complete PAA runs illustrate parameter specifications for both a standard analysis and for an analysis using the bootstrap validation procedures. Six references and four appendixes are provided.
Index Term(s): Computer languages; Computer program models; Computer software; Prediction
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