The Effect of CS Administration or an R-Optimized Alternative on R–PAS Variables: A Meta-Analysis of Findings From Six Studies

ABSTRACT

Controlling the number of Rorschach responses (R) as a method to reduce variability in the length of records has stimulated controversy among researchers for many years. Recently, the Rorschach Performance Assessment System (R–PAS; Meyer, Viglione, Mihura, Erard, & Erdberg, 2011) introduced an R-Optimized method to reduce variability in R. Using 4 published and 2 previously unpublished studies (N = 713), we examine the extent to which 51 Comprehensive System–based scores on the R–PAS profile pages are affected as a result of receiving Comprehensive System (CS; Exner, 2003) administration versus a version of R-Optimized administration. As hypothesized, R—the intended target of R-Optimized administration—showed reliable weighted average differences across each method of administration. As expected, its mean modestly increased and its standard deviation notably decreased. Also as hypothesized, the next largest effects were decreases in the variability (SD) of 2 variables directly related to R, R8910% and Complexity. No other reliable differences were observed. Therefore, because R-Optimized administration does not notably modify the existing CS-based normative values for other profiled R–PAS variables, the data do not support concerns that R-Optimized administration notably modifies the Rorschach task or that existing CS research data would not generalize to R–PAS. However, because R-Optimized administration reduces variability in R, it allows a single set of norms to apply readily to more people.

Disclosure

Gregory J. Meyer, Donald J. Viglione, and Joni L. Mihura own shares in the company that possesses rights to Rorschach Performance Assessment System.

Notes

¹ Asking for the card back after four responses and giving a reminder is called a “Pull” in R–PAS and in this article.

² Complexity is a rationally based, composite variable associated with the respondent's effort and engagement in the task that represents the total amount of differentiation and integration in the entire Rorschach record (Viglione & Meyer, 1998). Empirically, it also is an excellent marker of the first unrotated principal component among CS or R–PAS variables (Meyer, 1992b; Meyer et al., 2011).

³ However, the average effect size computed across variables within a study, as given in the final row of Table 5, provides a clue. For each study, the average values are close to the null values that would be expected if there was no difference. Thus, for each study the average of the g values is near zero, and the average of the SD proportions is close to 1.0 in all studies except Dean et al. (2007).