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Assessing the effectiveness of statistical classification techniques in predicting future employment of participants in the temporary assistance for needy families program / Isaac D. Montoya

By: Series: Journal of Employment Counseling. 45 : 2, pages 67-78 Publication details: June 2008Content type:
  • text
Media type:
  • volume
Carrier type:
  • unmediated
Subject(s): Summary: 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.
Item type: Articles
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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.

Psychology.

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