Teaching How to Derive Directly Interpretable Coding Schemes for Multiple Regression Analysis

Ronald C. Serlin and Joel R. Levin

Journal of Educational and Behavioral Statistics, 1985, vol. 10, issue 3, 223-238

Abstract: Multiple linear regression is a versatile model for encompassing analysis of variance, analysis of covariance, and aptitude-by-treatment interaction designs. The question of how to teach the coding of levels of a qualitative variable is addressed in this paper. Although a variety of coding schemes will produce invariant omnibus statistical results for a given set of data, one’s interpretation of treatment effects and treatment differences depends on the particular code values chosen. A general procedure is presented that allows the user to generate, on an a priori basis, code values that result in directly interpretable estimates of interest.

Keywords: Multiple regression; coded variables; teaching regression (search for similar items in EconPapers)
Date: 1985
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Persistent link: https://EconPapers.repec.org/RePEc:sae:jedbes:v:10:y:1985:i:3:p:223-238

DOI: 10.3102/10769986010003223

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