The analysis of errors in short-term motor memory research using trial profiles

In the past, researchers have debated the problem of selecting the most appropriate error measure (e.g., CE, VE, AE, or E) for use as the dependent variable when analyzing the results of their experiments in short-term motor memory research (Gessaroli & Schutz, 1982; Henry, 1974; Safrit, Spray, & Diewert, 1980; Schutz, 1977; Schutz & Roy, 1973). This paper suggests that the subjects' error scores, recorded over a series of trials, are analyzed individually, using repeated measures (RM) ANOVA. This analysis divides the total error sum of squares into recognizable components that, when identified, adequately explain the subjects' performance. The between-subjects sources of variation will indicate any differences in CE bias between the levels of each factor in the experiment. Similarly, any VE differences between the levels of each factor will be identified by significant trial-by-factor interactions. However, not all significant trial-by-factor interactions will necessarily indicate differences in VE performances. Nevertheless by plotting the group's perceived mean trial profiles for any significant trial-by-factor interactions, valuable insight can be gained into difference performance responses in trial adaptation for each level of the factors in the experimental design.