THE EFFECT OF FACTOR SCORES, GUTTMAN SCORES, AND SIMPLE SUM SCORES ON THE SIZE OF F RATIOS IN AN ANALYSIS O F VARIANCE DESIGN

Abstract

Many questions in the social sciences reduce to a comparison of mean values across groups in a classical analysis of variance F test. Often the original data my come from a set of items in a questionnaire or personality inventory. When this occurs, some sort of data reduction, combining of items, or scaling procedure is first performed before the hypothesis of no difference in mean values across groups can be made. In many cases, this problem causes undue concern t0 a researcher because the effect of the scoring procedure on the distribution of F is not clear. To help solve this problem, this study was undertaken to investigate whether the method used to calculate scores has any effect on the magnitude of the F ratio in an analysis of variance, for, if it were shown that no statistical difference existd, then a researcher would have some justification for showing the procedure having minimal messes. On the other hand, if statistical differences were b arise because of the kind d scaling procedure employed, then a researcher would have to be more cautious in his choice. For this empirical investigation, Guttman, Saaotor, and simple sum scores were generated using item responses from a large pool of high school seniors. No difference in scoring method was detected when the F ratios resulting from each of the three scoring methods were analyzed. This suggests that, for chin analyses, a simple sum score may be as effective as mres derived by more complicated methods.