A Comparison Between Comprehensive System and an Early Version of the Rorschach Performance Assessment System Administration With Outpatient Children and Adolescents

Abstract

For many years, the effects of variability in the length of Rorschach records has been debated, and a new administration procedure aimed at reducing the proportion of short and long records has recently been introduced. Using an outpatient sample of children and adolescents, the current study explored the impact of this new administration, found in the Rorschach Performance Assessment System (R-PAS), on the central tendencies of Rorschach variables. Specifically, the mean values of 51 variables in 142 Comprehensive System vs. 99 R-PAS collected records were compared with each other. Results showed comparable mean values across CS and R-PAS administration methods for the variables that guide interpretation with children and adolescents.Both methods produced an equivalent number of long (>27 responses) records. The only relevant difference that emerged is that the R-PAS administration yielded significantly fewer short (14-16 responses) records and lower variability in the number of responses.

The Association of Gender, Ethnicity, Age, and Education With Rorschach Scores

“…The mean intraclass correlations across all coders ranged from good to excellent (.69 to .87) and across the three most experienced judges it was excellent for all variables (.79 to .93; Meyer et al, 2011). Inter-rater reliability for the Adult Clinical Sample was reported by Meyer (1997Meyer ( , 1999 Reese et al (2014), and the results indicated that most of the variables (i.e., 44) had excellent inter-rater reliability (i.e., ICCs greater than .74), with the remaining variables (7) having good inter-rater reliability (i.e., ICCs between .60 and .74).…”

“…First, records from the two adult samples were statistically modeled to approximate the R-Optimized administration procedures found in R-PAS. Although research has consistently shown that the modeling procedure is accurate and does not greatly impact the results (e.g., see Meyer et al, 2011;Reese et al, 2014;Viglione, Giromini, Gustafson, & Meyer, 2014;Viglione, Perry, Giromini, & Meyer, 2011) Third, our samples were designed a priori to study demographic influences. Accordingly, effect sizes might be mitigated by uncontrolled methodological influences, such as levels of psychopathology obscuring stronger age or education effects.…”

Introducing a Bayesian Approach to Determining Degree of Fit With Existing Rorschach Norms

“…Bayesian analyses are still uncommon in the psychological and Rorschach literature (although see Reese, Viglione, & Giromini, 2014). However, a number of statisticians have recently demonstrated that classic null-hypothesis significance tests (NHSTs) are biased toward rejection, in that they underestimate the support for the null hypothesis, and overstate the evidence against it (e.g., Berger & Sellke, 1987;Edwards, Lindman, & Savage, 1963;Goodman, 1999;Rouder & Morey, 2011;Rouder, Speckman, Sun, Morey, & Iverson, 2009;Sellke, Bayarri, & Berger, 2001;Wagenmakers, 2007;Wagenmakers & Grünwald, 2006).…”

Introducing the concept of neurobiological foundation of Rorschach responses using the example of Oral Dependent Language

“…As such, our discussion of the findings mainly focused on patterns of effect size estimates and statistical significance, rather than results of individual analysis. Although null-hypothesis significance testing has been widely criticized by statisticians (Rouder & Morey, 2011;Rouder, Speckman, Sun, Morey & Iverson, 2009;Sellke, Bayarri & Berger, 2001;Wagenmakers, 2007;Wagenmakers & Gr€ unwald, 2006; see also Giromini, Viglione & McCullaugh, 2015;Reese, Viglione & Giromini, 2014), additional data are sorely needed prior to concluding with enough certainty that production of ODL responses associates with activation of dependency-related brain regions. Second, but related to the first point, our analyses could not examine all Page 1 and Page 2 R-PAS codes, because not all of them were suitable to our approach to data analysis.…”