Mutilating Data and Discarding Variance: The Dangers of Dichotomizing Continuous Variables.

This paper reviews issues involved in converting continuous variables to nominal variables to be used in the OVA techniques. The literature dealing with the dangers of dichotomizing continuous variables is reviewed. First, the assumptions invoked by OVA analyses are reviewed in addition to concerns regarding the loss of variance and a reduction in score reliability that result from the conversion of continuous variables to nominal variables. Second, regression is discussed as a more adequate alternative to analysis of variance (ANOVA) . Finally, a heuristic data set is presented and used as a demonstration of three alternatives that can occur through this conversion and when ANOVA is used. (Contains 6 figures and 20 references.) (Author/SLD) Reproductions supplied by EDRS are the best that can be made from the original document. Ncf) 2 1Dichotomizing Continuous Variables 1 Running head: DICHOTOMIZING CONTINUOUS VARIABLES PERMISSION TO REPRODUCE AND DISSEMINATE THIS MATERIAL HAS BEEN GRANTED BY TO THE EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) 1 U.S. DEPARTMENT OF EDUCATION Office of Educational Research and Improvement EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC) tillhis document has been reproduced as received from the person or organization originating it. 0 Minor changes have been made to improve reproduction quality. Points of view or opinions stated in this document do not necessarily represent official OERI position or policy. Mutilating Data and Discarding Variance: The Dangers of Dichotomizing Continuous Variables Michael W. Kroff Texas A&M University Paper presented at the annual meeting of the Southwest Educational Research Association, Austin, TX, February 14, 2002. BEST COPY AVAILABLE 2 Dichotomizing Continuous Variables 2 Abstract The present paper reviews issues involved in converting continuous variables to nominal variables to be used in OVA techniques. The literature dealing with the dangers of dichotomizing continuous variables is reviewed. First, the assumptions invoked by OVA analyses are reviewed in addition to concerns regarding the loss of variance and a reduction in score reliability that result from the conversion of continuous variables to nominal variables. Second, regression is discussed as a more adequate alternative to ANOVA. Finally, a heuristic data set is presented and used as a demonstration of three alternatives that can occur through this conversion and when ANOVA is employed.The present paper reviews issues involved in converting continuous variables to nominal variables to be used in OVA techniques. The literature dealing with the dangers of dichotomizing continuous variables is reviewed. First, the assumptions invoked by OVA analyses are reviewed in addition to concerns regarding the loss of variance and a reduction in score reliability that result from the conversion of continuous variables to nominal variables. Second, regression is discussed as a more adequate alternative to ANOVA. Finally, a heuristic data set is presented and used as a demonstration of three alternatives that can occur through this conversion and when ANOVA is employed.