2013
DOI: 10.1177/0748175612468594
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An Analysis of Cross Racial Identity Scale Scores Using Classical Test Theory and Rasch Item Response Models

Abstract: Item response models (IRMs) were used to analyze Cross Racial Identity Scale (CRIS) scores. Rasch analysis scores were compared with classical test theory (CTT) scores. The partial credit model demonstrated a high goodness of fit and correlations between Rasch and CTT scores ranged from .91 to .99. CRIS scores are supported by both methods.

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Cited by 10 publications
(7 citation statements)
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“…In 1992, Sabnani and Ponterotto criticized the instruments in the literature assessing ethnic-racial minority constructs for poor psychometric properties. However, scores on the CRIS (Vandiver et al, 2000) have been examined and supported in several psychometric studies (Gardner-Kitt & Worrell, 2007; Sussman, Beaujean, Worrell, & Watson, 2013; Worrell, Andretta, & Woodland, 2014; Worrell, Mendoza-Denton, Telesford, Simmons, & Martin, 2011). Thus, the CRIS, which has been described as an exemplar cultural identity instrument (Ponterotto & Park-Taylor, 2007) and a key instrument for cultural identity content (Umaña-Taylor et al, 2014), was used as a basis for developing the CERIS-A.…”
Section: Psychometric Properties Of Ceris-a Scoresmentioning
confidence: 99%
“…In 1992, Sabnani and Ponterotto criticized the instruments in the literature assessing ethnic-racial minority constructs for poor psychometric properties. However, scores on the CRIS (Vandiver et al, 2000) have been examined and supported in several psychometric studies (Gardner-Kitt & Worrell, 2007; Sussman, Beaujean, Worrell, & Watson, 2013; Worrell, Andretta, & Woodland, 2014; Worrell, Mendoza-Denton, Telesford, Simmons, & Martin, 2011). Thus, the CRIS, which has been described as an exemplar cultural identity instrument (Ponterotto & Park-Taylor, 2007) and a key instrument for cultural identity content (Umaña-Taylor et al, 2014), was used as a basis for developing the CERIS-A.…”
Section: Psychometric Properties Of Ceris-a Scoresmentioning
confidence: 99%
“…There is also considerable validity evidence in support of CRIS scores in the literature. The six-factor structure has been supported using both classical test theory and item response theory (Simmons et al, 2008;Sussman et al, 2013;Vandiver et al, 2002) in samples in the United States, and the factor structure has also been supported in a Black sample in Jamaica (Worrell & MacFarlane, 2017). Convergent validity for CRIS scores has been established with MIBI scores (Sellers et al, 1997) and scores of the Multigroup Ethnic Identity Measure (Phinney, 1992;see Vandiver et al, 2002;Worrell & Gardner-Kitt, 2006), and discriminant validity analyses have shown that CRIS scores are not strongly associated with the Big Five or social desirability (Vandiver et al, 2002).…”
Section: Methodsmentioning
confidence: 92%
“…There is substantial psychometric evidence in support of the six CRIS subscale scores in the extant literature. CRIS scores have been found to be internally consistent in adolescent, emerging adult, and adult samples (e.g., Worrell, 2008; Worrell et al, 2014; Worrell et al, 2004) and structural validity has been supported using exploratory factor analyses (Gardner-Kitt & Worrell, 2007; Simmons et al, 2008; Worrell et al, 2004), confirmatory factor analyses (CFAs; e.g., Vandiver et al, 2002; Worrell et al, 2011; Worrell et al, 2014; Worrell & Watson, 2008), and item response theory (Sussman et al, 2013). Research has also demonstrated that the scores are not substantially affected by social desirability (Vandiver et al, 2002), or by demographic characteristics (Fhagen-Smith et al, 2010).…”
mentioning
confidence: 99%
“…When there is good model-data-fit, measures produced by the instrument are interval, the interval scale measures have precise measurement errors for both individual items and subjects, allowing for inferential statistical analyses to be conducted with more power. Compared with classical test theory (CTT), Rasch models have several advantages [53], i.e., while the Classical Test Theory (CTT) analyses attach less importance to the functioning of specific items [54]. Rasch analyses can identify poor patterns of items and person performance, i.e., inform how well the model fits the data, and detect weak, biased, redundant items [55][56].…”
Section: Discussionmentioning
confidence: 99%