In empirical applications of structural equation modeling researchers often assume that the sample under investigation is homogenous unless observed charateristics allow for a division of the sample into mutual exclusive homogenous subgroups. If such information is not available, unobserved heterogeneity can be taken into account by a, finite-mixture approach (Arminger et al. (1998); Jedidi et al. (1997)). The simulation study presented in this paper reveals that this approach clearly outperforms a sequential procedure combining cluster and multigroup analysis.
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North Carolina State Univ, Dept Stat, Cary, NC USANorth Carolina State Univ, Dept Stat, Cary, NC USA
Luo, S.
Song, R.
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North Carolina State Univ, Dept Stat, Cary, NC USANorth Carolina State Univ, Dept Stat, Cary, NC USA
Song, R.
Styner, M.
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Univ N Carolina, Dept Psychiat, Chapel Hill, NC 27515 USANorth Carolina State Univ, Dept Stat, Cary, NC USA
Styner, M.
Gilmore, J. H.
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Univ N Carolina, Dept Comp Sci, Chapel Hill, NC 27515 USANorth Carolina State Univ, Dept Stat, Cary, NC USA
Gilmore, J. H.
Zhu, H.
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Univ N Carolina, Dept Biostat, Biomed Res Imaging Ctr, Chapel Hill, NC 27515 USA
Univ Texas MD Anderson Canc Ctr, Dept Biostat, Houston, TX 77030 USANorth Carolina State Univ, Dept Stat, Cary, NC USA