Psychometric Evaluation of the HIV Disclosure Belief Scale: A Rasch Model Approach

Hu, Jinxiang; Serovich, Julianne M.; Chen, Yi-Hsin; Brown, Monique J.; Kimberly, Judy A.

doi:10.1007/s10461-016-1478-7

Cited by 5 publications

(2 citation statements)

References 37 publications

(30 reference statements)

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“…Outfit values were also good except item 11 was slightly under 0.5(0.46). Because the infit statistics are more sensitive to unexpected observations of persons on items that match their ability level [45], infit statistics are more informative when investigating the fit of the items to the Rasch model [51][52][53]. Therefore, item 11 was kept in the scale.…”

Section: Model Fitmentioning

confidence: 99%

Validity Study of the R-PLA, a Resilience Scale for People Living with HIV

Serovich

Brown

et al. 2019

J HIV AIDS

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For HIV researchers seeking a better understanding of resilience so as to improve the lives of women living with HIV, a psychometrically sound measure is important. Numerous measures of resilience are currently available, and each has been developed for specific purposes or populations. For example, scales have been developed for measuring resilience in the general population, such as the Connor-Davidson Resilience Scale (CD-RISC) [21,22], the Resilience Scale (RS) [23], and the Brief Resilience Scale (BRS) [24]. Others have been more specific and geared toward certain populations, such as adults (e.g., Resilience Scale for Adults [RSA]) [25] and adolescents (e.g., Adolescent Resilience Scale [ARS]) [26]. A review study showed that as many instruments of different lengths exist to measure resilience among different populations, it is difficult to compare resilience across different studies, and no consensus exists about dimensionality [17]. For example, the CD-RISC has five dimensions (Personal competence, Trust, Positive Acceptance of Change, Control, and Spiritual Influence) and 25 items. The RS has two dimensions (Personal Competence and Acceptance of Self and Life) and 25 items. The BRS [24] has one dimension of resilience and 6 questions. In order to decrease administration time but still obtain psychometric stability of the CD-RISC, shorter versions of CD-RISC10 [27], CD-RISC2 [28] with 1 dimension were proposed and have been used in other studies [21,[29][30][31][32][33][34]. In addition, scales have been designed to be used with various medical conditions, such as chronic diseases of asthma or diabetes [35]. Researchers have been using scales such

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Section: Model Fitmentioning

confidence: 99%

Validity Study of the R-PLA, a Resilience Scale for People Living with HIV

Serovich

Brown

et al. 2019

J HIV AIDS

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“…Interestingly, those authors discussed multiple levels of invariance testing (e.g., configural, weak, strong, strict), yet reported results consistent with Muthén's (2013) suggestion above. Hu, Serovich, Chen, Brown, and Kimberly (2017) used ESEM to test the assumption of unidimensionality of the HIV Disclosure Belief Scale in the context of IRT, and Fonseca-Pedrero, Ortuño-Sierra, Mason, and Muñiz (2015) applied ESEM to confirm the hypothesized three-factor structure of the Oxford-Liverpool Inventory of Feelings and Experience. Although most of the studies we found involving dichotomous data took a confirmatory approach (e.g., Morin et al, 2013), Stanton and Watson (2017) used an exploratory approach to propose a two-factor model of the Mood Disorder Questionnaire.…”

Section: Factor Analysis and Internal Structurementioning

confidence: 99%

The Factorial Validity of the Cornell Critical Thinking Tests: A Multi-Analytic Approach

Leach

2019

Proceedings of the 2019 AERA Annual Meeting

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An unresolved issue in the measurement of critical thinking is the underlying factor structure of available instruments. The Cornell Critical Thinking Tests Level X (Ennis, Millman, & Tomko, 2005) is a widely used assessment of critical thinking in educational settings for students in grades 4-14. Perhaps due to the scale's intentional complex factor structure with overlapping dimensions, there is surprisingly limited empirical evidence is available on its dimensionality.Based on elementary student data (N = 2, 265), we used exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and exploratory structural equation modeling (ESEM) to examine the instrument's factor structure and compare results across procedures. ESEM yielded an interpretable factor solution that demonstrated measurement invariance across independent samples, whereas EFA and CFA procedures resulted in substantial item reduction and fewer interpretable factors. Implications to the selection and performance of factor analytic procedures for dimensionality assessment of non-simple structure data are discussed.

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