assessing the effectiveness of statistical classification techniques in predicting future employment of participants in the temporary assistance for needy families program |
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| Authors: | Isaac D. Montoya |
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| Affiliation: | Isaac D. Montoya, Affiliated Systems Corporation, Houston, Texas, and Department of Clinical Sciences & Administration, College of Pharmacy, Texas Medical Center, The University of Houston. Support for this research was provided by Grant R01‐DA11414 from the National Institute on Drug Abuse. |
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| Abstract: | Three classification techniques (Chi‐square Automatic Interaction Detection [CHAID], Classification and Regression Tree [CART], and discriminant analysis) were tested to determine their accuracy in predicting Temporary Assistance for Needy Families program recipients' future employment. Technique evaluation was based on proportion of correctly predicted cases and 6 other criteria. Sustained employment was associated with both recipients' subjective work‐related skills assessments and their objective test scores, and with their educational levels and marital status. Correct case classification by model was 74% for CHAID, 75% for CART, and 68% for discriminant analysis. Results suggest these classification tools can be useful supplements in assessments of clients' employment potentials. |
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