A step-down hierarchical multiple regression analysis for examining hypotheses about test bias in prediction

Lautenschlager, Gary J.
Mendoza, Jorge L.
1986
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A step-down hierarchical multiple regression analysis for examining hypotheses about test bias in prediction

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1986

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The problem of determining test bias in prediction using regression models is reexamined. Past approaches have made use of separate regression analyses in each subgroup, moderated multiple regression analysis using subgroup coding, and hierarchical multiple regression strategies. Although it is agreed that hierarchical multiple regression analysis is preferable to either of the former methods, the approach presented here differs with respect to the hypothesis testing procedure to be employed in such an analysis. This paper describes the difficulties in testing hypotheses about the existence of bias in prediction using step-up methods of analysis. Some shortcomings of previously recommended approaches for testing these hypotheses are discussed. Finally, a step-down hierarchical multiple regression procedure is recommended. Analysis of real data illustrates the potential usefulness of the step-down procedure.

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Applied Psychological Measurement, Volume 10, 1986

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Lautenschlager, Gary J & Mendoza, Jorge L. (1986). A step-down hierarchical multiple regression analysis for examining hypotheses about test bias in prediction. Applied Psychological Measurement, 10, 133-139. doi:10.1177/014662168601000202

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Lautenschlager, Gary J.; Mendoza, Jorge L.. (1986). A step-down hierarchical multiple regression analysis for examining hypotheses about test bias in prediction. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/102292.

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