Assessing Cross-Cultural Differences Through Use of Multiple-Group Invariance Analyses

Stein, Judith A.; Lee, Jerry; Jones, Patricia S.

doi:10.1207/s15327752jpa8703_05

Cited by 45 publications

(34 citation statements)

References 49 publications

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“…In order to test the consistency of measurement, the 15 factor, 78 indicator model was tested within the total sample as well as within multiple groups (random selection, gender, age, BMI; cf., Kline, 2011). Multiple-group invariance is an indicator for construct validity since it indicates that both the number of factors and the factor-indicator correspondence are the same within each sample (Byrne, 2008;Stein, Lee, & Jones, 2006). Moreover, to explore the relative importance of the different motives, mean levels were analyzed in dependence on gender, age, and BMI.…”

Section: Study 3: Testing Of the Eating Motivation Survey (Tems)mentioning

confidence: 99%

“…A stable measurement factor structure across different groups is an important source of evidence for construct validity (Byrne, 2008;Stein et al, 2006). Therefore, a subsequent step tested whether the factor loadings of the full and brief TEMS replicate across randomly divided groups, gender, age, and BMI [kg/m 2 ].…”

Section: Cross-validation: Testing Measurement Invariance Across Multmentioning

confidence: 99%

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Why we eat what we eat. The Eating Motivation Survey (TEMS)

et al. 2012

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a b s t r a c tUnderstanding why people select certain food items in everyday life is crucial for the creation of interventions to promote normal eating and to prevent the development of obesity and eating disorders. The Eating Motivation Survey (TEMS) was developed within a frame of three different studies. In Study 1, a total of 331 motives for eating behavior were generated on the basis of different data sources (previous research, nutritionist interviews, and expert discussions). In Study 2, 1250 respondents were provided with a set of motives from Study 1 and the Eating Motivation Survey was finalized. In Study 3, a sample of 1040 participants filled in the Eating Motivation Survey. Confirmatory factor analysis with fifteen factors for food choice yielded a satisfactory model fit for a full (78 items) and brief survey version (45 items) with RMSEA .048 and .037, 90% CI .047-.049 and .035-.039, respectively. Factor structure was generally invariant across random selected groups, gender, and BMI, which indicates a high stability for the Eating Motivation Survey. On the mean level, however, significant differences in motivation for food choice associated with gender, age, and BMI emerged. Implications of the fifteen distinct motivations to choose foods in everyday life are discussed.

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Section: Study 3: Testing Of the Eating Motivation Survey (Tems)mentioning

confidence: 99%

Section: Cross-validation: Testing Measurement Invariance Across Multmentioning

confidence: 99%

Why we eat what we eat. The Eating Motivation Survey (TEMS)

et al. 2012

View full text Add to dashboard Cite

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“…Multi-sample models-Covariance structure analysis has become the method of choice for assessing the comparability of measures in different groups through the testing of measurement invariance with varying degrees of stringency across groups (Yin and Fan 2003;Stein et al 2006). Using this methodology, one can specify an a priori factor model in two groups and test it for various degrees of invariance using structural modeling.…”

Section: 32mentioning

confidence: 99%

“…Establishing factorial invariance alone does not necessarily mean that different groups will report the same mean scores on a particular measurement instrument. Even if factor structures are similar across different groups, there may be a tendency to score higher or lower in a particular group (Handelsman et al 2005;Stein et al 2006). …”

Section: 32mentioning

confidence: 99%

Pain, problem drug use history, and aberrant analgesic use behaviors in persons living with HIV

Tsao

Stein²,

Dobalian

2007

Pain

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Little is known about the relationship between pain and aberrant use of prescription analgesics in persons living with HIV. We examined the predictive and concurrent associations among pain, aberrant use of opioids, and problem drug use history in a nationally representative longitudinal sample of 2267 HIV+ persons. Covariance structure analyses tested a conceptual model wherein HIV + patients with a history of problematic drug use (n = 870), compared to those without such history (n = 1397), were hypothesized to report more pain and aberrant opioid use, as well as use of opioids specifically for pain at baseline and 6 and 12 month follow-ups, after controlling for key sociodemographic characteristics. In support of the hypothesized model, patients with a history of problematic drug use reported more pain, and were more likely to report aberrant use of prescription analgesics, as well as use of such medications specifically for pain, compared to patients without such history. We also found a trend toward greater stability of aberrant opioid use over time in problem drug users compared with non-problem users suggesting a persistent pattern of inappropriate medication use in the former group. Our findings suggest that even though HIV+ persons with a history of problematic drug use report on-going patterns of using prescription analgesics specifically for pain, these patients continued to experience persistently higher levels of pain, relative to nonproblem users. Among non-problem users, pain was not linked to aberrant use of opioids, but was linked to the use of such medications specifically for pain.

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“…In the current study, we use latent variable confirmatory analytic techniques to assess and verify the psychometric properties of a multidimensional stigma questionnaire designed for service providers in China. Confirmatory factor analysis (CFA), which is a special case of structural equation modeling and extends well beyond a typical exploratory factor analysis (EFA), is the method of choice for validating the dimensionality of a factor structure that is hypothesized a priori or first developed in an EFA and then confirmed through CFA (Bentler and Stein 1992;Floyd and Widaman 1995;Stein et al 2006;Ullman 2006). The confirmatory model can be verified through use of various fit statistics that report whether a set of data conforms to the model that is imposed upon it and whether the factors represent separable dimensions of the proposed model.…”

Section: Introductionmentioning

confidence: 99%

Measuring HIV-related Stigma Among Chinese Service Providers: Confirmatory Factor Analysis of a Multidimensional Scale

Stein

2007

AIDS Behav

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An HIV-related stigma scale for health care workers needs to be multidimensional in that it should encompass attitudes that might be experienced by the general public about people living with HIV/ AIDS (PLWHA) (e.g., fear, shame, blame) and, further, specifically capture perceptions of appropriate professional care and medical responsibilities regarding PLWHA. A 17-item, 5-factor multidimensional HIV-related stigma scale was developed and validated using both exploratory and confirmatory factor analysis among 1,101 service providers in China. The sample was divided into a development sample (N = 551) and a validation sample (N = 550). The fit of the final confirmatory factor model with five hypothesized subscales was excellent in both samples. The final stigma subscales included: Discrimination Intent at Work, Opinion about Health Care for HIV/AIDS Patients, Prejudiced Attitudes, Internalized Shame, and Fear of PLWHA.

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Assessing Cross-Cultural Differences Through Use of Multiple-Group Invariance Analyses

Cited by 45 publications

References 49 publications

Why we eat what we eat. The Eating Motivation Survey (TEMS)

Why we eat what we eat. The Eating Motivation Survey (TEMS)

Pain, problem drug use history, and aberrant analgesic use behaviors in persons living with HIV

Measuring HIV-related Stigma Among Chinese Service Providers: Confirmatory Factor Analysis of a Multidimensional Scale

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