Imputing missing data values in repeated measurement within-subjects designs - Bingham, C. Raymond; Stemmler, Mark; Petersen, Anne C.; Graber, Julia A. (Methods of Psychological Research, 1998)
Introduces a procedure for inputing missing data values in repeated measurement within-subjects designs. Two sets of simulations were performed. The first used a single data set to examine the influence of the proportion of cases with missing values, the number of repeated measures, and the shape of the individual response curve on the discrepancy between the imputed and observed data, and to compare this method with mean-substitution. A Monte Carlo simulation was also conducted which examined the proportion of cases with missing values, the shape of the individual response curve, and the sample size in relation to the discrepancy between the observed and imputed standard errors and moments. Results indicated that the imputed data closely approximated observed values, that estimation improved as the number of repeated measures increased and proportion of cases with missing values decreased, and that sample sizes greater than 100 provided equivalent results.
Keywords: imputing missing data values; repeated measurement within subjects designs