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Abstract
A MIMIC model is developed that contains a one-dimensional latent variable measured by ordinal indicators. The latent variable can be either discrete and ordered or continuous. Parameters for both the measurement and structural components of the model are estimated simultaneously using the EM algorithm. An example of a sociological application is presented.
|
AGRESTI, A.
(1983) “A survey of strategies for modeling cross-classifications having ordinal variables.” J. of the Amer. Stat. Assn. 78 (March): 184-198. Google Scholar | Crossref | |
|
BOCK, R. D.
and M. AITKIN (1981) “Marginal maximum likelihood estimation of item parameters: application of an EM algorithm.” Psychometrika 46 (December): 443-459. Google Scholar | Crossref | |
|
BOCK, R. D.
and M. LIEBERMAN (1970) “Fitting a response model for n dichotomously scored items.” Psychometrika 35 (June): 179-197. Google Scholar | Crossref | |
|
BYE, B. V.
and E. SCHECHTER (1982) 1978 Survey of Disability and Work Technical Introduction. SSA Publication No. 13-11745 (January). Google Scholar | |
|
GLOGG, C. C.
(1979) “Some latent structure models for the analysis of Likert-type data.” Social Sci. Research 8: 287-301. Google Scholar | Crossref | |
|
GLOGG, C. C.
and L. A. GOODMAN (1984) “Latent structure analysis of a set of multidimensional contingency tables.” J. of Amer. Stat. Assn. 79 (December): 762-771. Google Scholar | |
|
DEMPSTER, A P.
, N. M. LAIRD , and D. B. RUBIN (1977) “Maximum likelihood from incomplete data via the EM algorithm.” J. of the Royal Stat. Society (Series B) 39: 1-38. Google Scholar | |
|
FIENBERG, S. E.
(1977) The Analysis of Cross-Classified Categorical Data. Cambridge, MA: MIT Press. Google Scholar | |
|
HECKMAN, J.J.
and B. SINGER (1982) “Structural analysis of longitudinal data,” pp. 39-77 in Advances in Econometrics. Cambridge: Cambridge Univ. Press. Google Scholar | |
|
JÖRESKOG, K. G.
and A. S. GOLDBERGER (1975) “Estimation of a model with multiple indicators and multiple causes of a single latent variable.” J. of the Amer. Stat. Assn. 70 (September): 631-639. Google Scholar | |
|
JÖRESKOG, K. G.
and A. S. GOLDBERGER (1978) LISREL: Analysis of Linear Structural Relationships by the Method of Maximum Likelihood. Washington, DC: National Education Resources. Google Scholar | |
|
JÖRESKOG, K. G.
and D. SORBOM (1979) Advances in Factor Analysis and Structural Equation Models. Cambridge: Abt Books. Google Scholar | |
|
KOLAKOWSKI, D.
and R. D. BOCK (1973) LOGOG: Maximum Likelihood Item Analysis and Test Scoring-Logistic Model for Multiple Item Responses. Washington, DC: National Education Resources. Google Scholar | |
|
LAIRD, N.
(1978) “Nonparametric maximum likelihood estimation of a mixing distribution.” J. of the Amer. Stat. Assn. 73 (December): 805-810. Google Scholar | Crossref | |
|
LEE, L.
(1982) “Health and wage: a simultaneous equation model with multiple discrete indicators.” Int. Econ. Rev. 23 (February): 199-221. Google Scholar | Crossref | |
|
McCULLAGH. P.
(1980) “Regression models for ordinal data.” J. of the Royal Stat. Society, B. 42, 2: 109-142. Google Scholar | |
|
MUTHÉN, B.
(1984) “A general structural equation model with dichotomous ordered categorical and continuous latent variable indicators.” Psychometrika 49 (March): 115-132. Google Scholar | Crossref | |
|
MUTHÉN, B.
and A. CHRISTOFFERSSON (1981) “Simultaneous factor analysis of dichotomous variables in several groups.” Psychometrika 46 (December): 407-419. Google Scholar | Crossref |
