Premium
TESTING FOR FAIRNESS WITH A MODERATED MULTIPLE REGRESSION STRATEGY: AN ALTERNATIVE TO DIFFERENTIAL ANALYSIS 1
Author(s) -
BARTLETT C. J.,
BOBKO PHILIP,
MOSIER STEVEN B.,
HANNAN ROBERT
Publication year - 1978
Publication title -
personnel psychology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.076
H-Index - 142
eISSN - 1744-6570
pISSN - 0031-5826
DOI - 10.1111/j.1744-6570.1978.tb00442.x
Subject(s) - bivariate analysis , statistics , regression analysis , regression , psychology , correlation , econometrics , coding (social sciences) , test (biology) , differential (mechanical device) , linear regression , social psychology , mathematics , paleontology , geometry , engineering , biology , aerospace engineering
It is argued that analyses of subgroup differences utilizing a bivariate correlation strategy do not provide an adequate examination of test fairness. An analysis of differential prediction, which involves slopes and intercepts of regression lines results in more complete coverage of the test fairness issue, since the overall regression line determines the way in which a test is used for prediction. While subgroup correlation coefficients yield information concerning the slopes and intercepts, means and standard deviations must also be examined. A moderated multiple regression strategy is recommended as an alternative to separate analyses by subgroups. An ordered step‐up regression procedure is presented which is more encompassing than the bivariate strategies, while avoiding inherent problems associated with subgroup coding in multiple regression.