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A study was conducted to implement the use of a standardized effect size and corresponding classification guidelines for polytomous data with the POLYSIBTEST procedure and compare those guidelines with prior recommendations. Two simulation studies were included. The first identifies new unstandardized test heuristics for classifying moderate and large differential item functioning (DIF) for polytomous response data with three to seven response options. These are provided for researchers studying polytomous data using POLYSIBTEST software that has been published previously. The second simulation study provides one pair of standardized effect size heuristics that can be employed with items having any number of response options and compares true-positive and false-positive rates for the standardized effect size proposed by Weese with one proposed by Zwick et al. and two unstandardized classification procedures (Gierl; Golia). All four procedures retained false-positive rates generally below the level of significance at both moderate and large DIF levels. However, Weese's standardized effect size was not affected by sample size and provided slightly higher true-positive rates than the Zwick et al. and Golia's recommendations, while flagging substantially fewer items that might be characterized as having negligible DIF when compared with Gierl's suggested criterion. The proposed effect size allows for easier use and interpretation by practitioners as it can be applied to items with any number of response options and is interpreted as a difference in standard deviation units., Competing Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2022.)

A simulation study was conducted to investigate the heuristics of the SIBTEST procedure and how it compares with ETS classification guidelines used with the Mantel-Haenszel procedure. Prior heuristics have been used for nearly 25 years, but they are based on a simulation study that was restricted due to computer limitations and that modeled item parameters from estimates of ACT and ASVAB tests from 1987 and 1984, respectively. Further, suggested heuristics for data fitting a two-parameter logistic model (2PL) have essentially went unused since their original presentation. This simulation study incorporates a wide range of data conditions to recommend heuristics for both 2PL and three-parameter logistic (3PL) data that correspond with ETS's Mantel-Haenszel heuristics. Levels of agreement between the new SIBTEST heuristics and Mantel-Haenszel heuristics were similar for 2PL data and higher than prior SIBTEST heuristics for 3PL data. The new recommendations provide higher true-positive rates for 2PL data. Conversely, they displayed decreased true-positive rates for 3PL data. False-positive rates, overall, remained below the level of significance for the new heuristics. Unequal group sizes resulted in slightly larger false-positive rates than balanced designs for both prior and new SIBTEST heuristics, with rates less than alpha levels for equal ability distributions and unbalanced designs versus false-positive rates slightly higher than alpha with unequal ability distributions and unbalanced designs., Competing Interests: Declaration of Conflicting Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2021.)

Colleges are rape-prone cultures with high rates of sexual victimization. Fraternities' and sororities' relationships with sexual assault are consistent themes in literature focusing on sexual violence among college students. Previous research suggests that fraternity men are more likely to endorse rape-supportive attitudes compared with non-Greek men or sorority women. The present study examines rape-supportive attitudes as well as rape and sexual assault victimization in college students with a focus on gender and Greek-life (i.e., involvement in fraternities or sororities) status variables. College students ( N = 1,002) completed a survey including the Token Resistance to Sex Scale (TRSS), Illinois Rape Myth Acceptance Scale-Short Form (IRMA-S), and items related to past experiences of nonconsensual sex. Two regression models tested predictors of token resistance and rape myth acceptance. Chi-square analyses tested between-group differences of experiencing rape and sexual assault. Gender ( p < .001), Greek status ( p < .001), and race/ethnicity ( p < .001) were predictors for TRSS scores. For IRMA scores, gender ( p < .001), Greek status ( p < .001), and race/ethnicity variables ( p < .001) were also significant. Interaction terms revealed that Greek men had higher token resistance and rape myth acceptance than any other group. Chi-square analyses indicate women more frequently report experiences of rape (χ 2 = 25.57, df = 1, p < .001) and sexual assault (χ 2 = 31.75, df = 1, p < .001). Men report high rates (40.8%) of experiencing sexual assault "because refusing was useless." No differences of victimization rates were found between Greeks and non-Greeks. Gender and sexual scripting theory can help explain gender differences in attitudes and experiences. Greater endorsement of rape myth acceptance and token resistance by Greeks, who influence college party culture, could be contributing to a culture conducive to rape. Findings demonstrate a continued need for interventions focused on shifting sociocultural dynamics (e.g., traditional roles and sexual scripting) on college campuses.