482 research outputs found

    Factor copula models for item response data

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    Factor or conditional independence models based on copulas are proposed for multivariate discrete data such as item responses. The factor copula models have interpretations of latent maxima/minima (in comparison with latent means) and can lead to more probability in the joint upper or lower tail compared with factor models based on the discretized multivariate normal distribution (or multidimensional normal ogive model). Details on maximum likelihood estimation of parameters for the factor copula model are given, as well as analysis of the behavior of the log-likelihood. Our general methodology is illustrated with several item response data sets, and it is shown that there is a substantial improvement on existing models both conceptually and in fit to data

    The structure of PGC Morale Scale in American and Japanese aged: A further note

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    This study involves a further replication of cross-cultural comparison of the structure of the Philadelphia Geriatric Center Morale Scale (PGCMS). Using Japanese and American data sets, the present research replicates and extends the findings reported by Liang et al. (1987). In particular, the earlier findings that four PGCMS items behave differently in two cultures are replicated. The present study yields two additional observations. First, the invariance in the PGCMS can now be extended beyond the urban elderly residents studied by Liang et al. (1987) to the entire aged population in the U.S. and Japan. Second, this comparability is robust despite the elimination of correlated measurement errors from the earlier specifications and when several exogenous variables are controlled. Further, the impact of selected demographic variables on the PGCMS was evaluated. In addition, qualitative data from in-depth interviews provide further insights concerning the cultural differences in the expression of well-being.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/42991/1/10823_2004_Article_BF00116576.pd
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