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Basic Programs for Prediction Analysis of Cross Classification

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Basic Programs for Prediction Analysis of Cross Classification

Auteurs : Alexander Von Eye ; Gunter Krampen

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DOI: 10.1177/0013164487471021

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<meta-value> EDUCATIONAL AND PSYCHOLOGICAL MEASUREMENT 1987, 47 BASIC PROGRAMS FOR PREDICTION ANALYSIS OF CROSS CLASSIFICATION ALEXANDER VON EYE College of Human Development The Pennsylvania State University GUNTER KRAMPEN University of Trier, West Germany PREDICTION analysis of cross classifications (PA) is a procedure to test simultaneous point predictions. The method was originally proposed by Hildebrand, Laing, and Rosenthal (1977a, 1977b). Modifications have been discussed that involve both descriptive and inferential measures (Brandtstadter and von Eye, in press; von Eye and Brandtstadter, 1985). PA has mostly been applied in develop- mental research (cf. Froman and Hubert, 1980). The purpose of the present paper is to describe five versions of BASIC microcomputer programs that perform different versions of PA. The computational procedures of the programs follow the descrip- tion in von Eye and Brandtstadter (1985). Except for Program Versions 4 and 5, the second part of Programs 1 and 2 (see below), the binomial test that replaces Hildebrand et al.'s (1977b) z-test approximation, and an additional, more flexible measure of predic- tion success, these procedures are equivalent to the ones described in Hildebrand et al. (1977b). The program computes expected frequencies using maximum likelihood estimators, performs the binomial test, and determines all descriptive measures. Description Input. Five versions of the program are available. Each of these versions is interactive and prompts for size of the matrix, observed Copyright 1987 Educational and Psychological Measurement 141 142 EDUCATIONAL AND PSYCHOLOGICAL MEASUREMENT frequencies, and the user must specify the cells that fulfill the prediction (hit cells). Output. The programs print the matrices of observed and expect- ed frequencies, the matrix of hit and error cells, descriptive mea- sures of prediction success, scope, and precision. The binomial test is performed. Finally, Hildebrand et al.'s (1977b) measure of predic- tion success is decomposed and descriptive measures are provided for each single prediction. Version 1. A PA is performed. In addition, a quasi-independence log-linear model is fitted, if df > 0. Here, error cells are considered structural zeros. Version 2. As Version 1; however, the results are displayed at the screen only. This version is particularly useful for users of laptop computers. Version 3. A PA is performed in which structural zeros can be taken into account in the estimation of expected frequencies. A log- linear model is fitted. This program is available also in a .EXE version (compiled BASIC). Version 4. A PA is performed as in Version 1. In addition, the user is prompted to identify ranks for the categories of either predictor, the criterion, or both. Then, expected frequencies are estimated, using the algorithm described in Fienberg (1980), and goodness of fit chi-square values are determined. This program is available also in a .EXE version. Version 5. An unconditional PA is performed. This variant of PA does not analyze implicative predictions. Rather, it analyzes the assumption that a set of cells in a two or higher dimensional contingency table contains more elements than expected by chance. Program Language and Requirements A first set of interpreted programs is written in MS GW BASIC. The compiled programs are written in MS compiled BASIC. They all have been implemented on a 272 K Bytes HPI 10 Portable under DOS 2.11. The programs occupy between approximately 5 K Bytes (Version 1) and approximately 10 K Bytes (Version 4 in .EXE form) of memory. A second set of equivalent versions of the programs is available in Applesoft BASIC. These versions have been imple- mented on Apple Ile and Apple lIc computers. Program Availability A GW BASIC program listing and sample output are available gratis from Alexander von Eye, The Pennsylvania State University, VON EYE AND KRAMPEN College of Human Development, S-i 10 Henderson Human Develop- ment Building, University Park, PA 16802. If you send a microdis- kette (3/2 inch), the programs will be copied on this diskette. The Applesoft programs and sample outputs are available gratis from Gunter Krampen, University of Trier, FB 1-Psychology, Tarforst, D-5500 Trier, West Germany. If you send a 51/4 inch diskette, the programs will be copied on this diskette. REFERENCES Brandtstadter, J. and von Eye, A. (in press). Hypothesenevaluation in der multivariaten Pradiktionsanalyse. Methodische Erweiter- ungen fur multivariate Anwendungen. Psychologische Beitrage. Fienberg, S. E. (1980). The analysis of cross classified categorical data (2nd ed.). Cambridge, MA: The MIT Press. Froman, T. and Hubert, L. J. (1980). Application of prediction analysis to developmental priority. Psychological Bulletin, 87, 136-146. Hildebrand, D. K., Laing, J. D., and Rosenthal, H. (1977a). Analysis of ordinal data. Beverly Hills, CA: Sage. Hildebrand, D. K., Laing, J. D., and Rosenthal, H. (1977b). Prediction analysis of cross classification. New York: Wiley. von Eye, A. and Brandtstadter, J. (1985). Aussagenlogische Analyse von Kontingenztafeln: IV. Die Beurteilung der statistischen Relevanz von Einzelpradiktoren in multivariaten Pradiktionen. Trierer Psychologische Berichte, 12, 1-24. 143 </meta-value>
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