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CHOICE OF VARIABLES AND GENDER DIFFERENTIATED PREDICTION WITHIN SELECTED ACADEMIC PROGRAMS
Author(s) -
GAMACHE LEANN M.,
NOVICK MELVIN R.
Publication year - 1985
Publication title -
journal of educational measurement
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.917
H-Index - 47
eISSN - 1745-3984
pISSN - 0022-0655
DOI - 10.1111/j.1745-3984.1985.tb01049.x
Subject(s) - differential (mechanical device) , predictive validity , statistics , selection (genetic algorithm) , differential effects , mathematics , psychology , econometrics , computer science , medicine , machine learning , engineering , aerospace engineering
The existence of differential prediction of 2‐year grade point average is reported for gender groups within programs of study at a large state university. Johnson‐Neyman analyses indicate regions on the predictor score scales where differential prediction has practical impact within each program. A significant portion of students is generally affected. It is shown that careful selection of a subset of variables reduces differential prediction while maintaining predictive potency.