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Summary and Analysis of Article

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The purpose of this quantitative study, "What happens If We Compare Chopsticks With Forks? The Impact of Making Inappropriate Comparisons in Cross-Cultural Research" (Chen, 2008) was to examine the direction and degree of bias resulting from various forms of non-variance in cross-cultural research. The author reports three major goals in the present investigation:

(a) To examine bias in regression slopes (beta weights) when factor loadings are not invariant, as factor loading invariance is a prerequisite for regression slope comparisons (e.g., When using self-esteem to predict subjective well-being, how would the predictive relationship be affected if the factor loadings of self-esteem were different across groups?);
(b) To explore bias in means when factor loadings are not invariant, because factor loading invariance is also a prerequisite for proper mean comparisons (e.g., How would group means be biased when factor loadings of self-esteem differ?);
(c) To investigate bias in means when intercepts (i.e., point of origin) are not invariant, as intercept invariance is a prerequisite for mean comparisons, in addition to factor loading invariance (Widaman & Reise, 1997; e.g., When one group has higher intercepts in self-esteem than the other group, in what direction would the means be biased in each group?) Given the computational complexity and intensity, the Mplus software program (Muthén & Muthén, 1998) was used to conduct the simulation

Chen (2008) investigated these three goals through three different studies. Findings from Study 1 indicate that lack of factor loading invariance can produce artificial interaction effects in predictive relationships. For example, self-esteem may be found to be a stronger predictor of life-satisfaction for Caucasians than for Chinese, when in fact the relationship is the same for both groups. Therefore, the construct validity of the scales is still in question, as they may measure different concepts in different cultures. Results of Studies 2 and 3 ...

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