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Volumn 13, Issue 3, 2006, Pages 325-351

A maximum likelihood approach for multisample nonlinear structural equation models with missing continuous and dichotomous data

Author keywords

[No Author keywords available]

Indexed keywords

MANAGEMENT RESEARCH; MAXIMUM LIKELIHOOD APPROACHES; MISSING AT RANDOMS; MODELING RELATIONS; NONLINEAR STRUCTURAL EQUATIONS; SIMULATION STUDIES; STRUCTURAL EQUATION MODELS; STRUCTURAL EQUATIONS;

EID: 33746387861     PISSN: 10705511     EISSN: None     Source Type: Journal    
DOI: 10.1207/s15328007sem1303_1     Document Type: Article
Times cited : (6)

References (43)
  • 1
    • 0036011444 scopus 로고    scopus 로고
    • Heterogenous factor analysis models: A Bayesian approach
    • Ansari, A., Jedidi, K., & Dube, L. (2002). Heterogenous factor analysis models: A Bayesian approach. Psychometrika, 67, 49-78.
    • (2002) Psychometrika , vol.67 , pp. 49-78
    • Ansari, A.1    Jedidi, K.2    Dube, L.3
  • 2
    • 0034257394 scopus 로고    scopus 로고
    • A hierarchical Bayesian methodology for treating heterogeneity in structural equation models
    • Ansari, A., Jedidi, K., & Jagpal, S. (2000). A hierarchical Bayesian methodology for treating heterogeneity in structural equation models. Marketing Science, 19, 328-347.
    • (2000) Marketing Science , vol.19 , pp. 328-347
    • Ansari, A.1    Jedidi, K.2    Jagpal, S.3
  • 3
    • 0000857692 scopus 로고
    • State versus action orientation and the theory of reasoned action: An application to coupon usage
    • Bagozzi, R. P., Baumgartner, H., & Yi, Y. (1992). State versus action orientation and the theory of reasoned action: An application to coupon usage. Journal of Consumer Research, 18, 505-517.
    • (1992) Journal of Consumer Research , vol.18 , pp. 505-517
    • Bagozzi, R.P.1    Baumgartner, H.2    Yi, Y.3
  • 9
    • 24944456035 scopus 로고    scopus 로고
    • Sensitivity of fit indexes of misspecified structural or measurement model components: Rationale of two-index strategy revisited
    • Fan, X., & Sivo, S. A. (2005). Sensitivity of fit indexes of misspecified structural or measurement model components: Rationale of two-index strategy revisited. Structural Equation Modeling, 12, 343-367.
    • (2005) Structural Equation Modeling , vol.12 , pp. 343-367
    • Fan, X.1    Sivo, S.A.2
  • 10
    • 0000736067 scopus 로고    scopus 로고
    • Simulating normalizing constant: From importance sampling to bridge sampling to path sampling
    • Gelman, A., & Meng, X. L. (1998). Simulating normalizing constant: From importance sampling to bridge sampling to path sampling. Statistical Science, 13, 163-185.
    • (1998) Statistical Science , vol.13 , pp. 163-185
    • Gelman, A.1    Meng, X.L.2
  • 11
    • 0000954353 scopus 로고
    • Efficient metropolis jumping rules
    • J. M. Bernardo, J. O. Berger, A. P. Dawid, & A. F. M. Smith (Eds.), Oxford, UK: Oxford University Press
    • Gelman, A., Roberts, G. O., & Gilks, W. R. (1995). Efficient metropolis jumping rules. In J. M. Bernardo, J. O. Berger, A. P. Dawid, & A. F. M. Smith (Eds.), Bayesian statistics (Vol. 5, pp. 599-607). Oxford, UK: Oxford University Press.
    • (1995) Bayesian Statistics , vol.5 , pp. 599-607
    • Gelman, A.1    Roberts, G.O.2    Gilks, W.R.3
  • 13
    • 0001178202 scopus 로고
    • A language and program for complex Bayesian modeling
    • Gilks, W. R., Thomas, A., & Spiegelhalter, D. J. (1994). A language and program for complex Bayesian modeling. Statistician, 43, 169-177.
    • (1994) Statistician , vol.43 , pp. 169-177
    • Gilks, W.R.1    Thomas, A.2    Spiegelhalter, D.J.3
  • 14
    • 77956890234 scopus 로고
    • Monte Carlo sampling methods using Markov chains and their application
    • Hastings, W. K. (1970). Monte Carlo sampling methods using Markov chains and their application. Biometrika, 57, 97-109.
    • (1970) Biometrika , vol.57 , pp. 97-109
    • Hastings, W.K.1
  • 15
    • 11944261983 scopus 로고
    • Measurement error in the analysis of interaction effects between continuous predictors using multiple regression: Multiple indicator and structural equation approaches
    • Jaccard, J., & Wan, C. K. (1995). Measurement error in the analysis of interaction effects between continuous predictors using multiple regression: Multiple indicator and structural equation approaches. Psychological Bulletin, 117, 348-357.
    • (1995) Psychological Bulletin , vol.117 , pp. 348-357
    • Jaccard, J.1    Wan, C.K.2
  • 18
    • 0000456985 scopus 로고
    • Estimating the nonlinear and interactive effects of latent variables
    • Kenny, D. A., & Judd, C. M. (1984). Estimating the nonlinear and interactive effects of latent variables. Psychological Bulletin, 96, 201-210.
    • (1984) Psychological Bulletin , vol.96 , pp. 201-210
    • Kenny, D.A.1    Judd, C.M.2
  • 19
    • 24944586514 scopus 로고    scopus 로고
    • The relation among fix indexes, power, and sample size in structural equation modeling
    • Kim, K. H. (2005). The relation among fix indexes, power, and sample size in structural equation modeling. Structural Equation Modeling, 12, 368-390.
    • (2005) Structural Equation Modeling , vol.12 , pp. 368-390
    • Kim, K.H.1
  • 20
    • 0034867298 scopus 로고    scopus 로고
    • Maximum likelihood estimation of two-level latent variable models with mixed continuous and polytomous data
    • Lee, S. Y., & Shi, J. Q. (2001). Maximum likelihood estimation of two-level latent variable models with mixed continuous and polytomous data. Biometrics, 57, 787-794.
    • (2001) Biometrics , vol.57 , pp. 787-794
    • Lee, S.Y.1    Shi, J.Q.2
  • 21
    • 0035528598 scopus 로고    scopus 로고
    • Hypothesis testing and model comparison in two-level structural equation models
    • Lee, S. Y., & Song, X. Y. (2001). Hypothesis testing and model comparison in two-level structural equation models. Multivariate Behavioral Research, 36, 639-655.
    • (2001) Multivariate Behavioral Research , vol.36 , pp. 639-655
    • Lee, S.Y.1    Song, X.Y.2
  • 22
    • 0038457409 scopus 로고    scopus 로고
    • Bayesian model selection for mixtures of structural equation models with an unknown number of components
    • Lee, S. Y., & Song, X. Y. (2003). Bayesian model selection for mixtures of structural equation models with an unknown number of components. British Journal of Mathematical and Statistical Psychology, 56, 145-165.
    • (2003) British Journal of Mathematical and Statistical Psychology , vol.56 , pp. 145-165
    • Lee, S.Y.1    Song, X.Y.2
  • 23
    • 4444348036 scopus 로고    scopus 로고
    • Maximum likelihood analysis of a general latent variable model with hierarchically mixed data
    • Lee, S. Y., & Song, X. Y. (2004). Maximum likelihood analysis of a general latent variable model with hierarchically mixed data. Biometrics, 60, 624-636.
    • (2004) Biometrics , vol.60 , pp. 624-636
    • Lee, S.Y.1    Song, X.Y.2
  • 24
    • 3042735142 scopus 로고    scopus 로고
    • Comparison of approaches in estimating interaction and quadratic effects of latent variables
    • Lee, S. Y., Song, X. Y., & Poon, W. Y. (2004). Comparison of approaches in estimating interaction and quadratic effects of latent variables. Multivariate Behavioral Research, 39, 37-67.
    • (2004) Multivariate Behavioral Research , vol.39 , pp. 37-67
    • Lee, S.Y.1    Song, X.Y.2    Poon, W.Y.3
  • 26
    • 0035998148 scopus 로고    scopus 로고
    • Maximum likelihood estimation of nonlinear structural equation models
    • Lee, S. Y., & Zhu, H. T. (2002). Maximum likelihood estimation of nonlinear structural equation models. Psychometrika, 67, 189-210.
    • (2002) Psychometrika , vol.67 , pp. 189-210
    • Lee, S.Y.1    Zhu, H.T.2
  • 28
    • 0001044972 scopus 로고
    • Finding the observed information matrix when using em algorithm
    • Louis, T. A. (1982). Finding the observed information matrix when using EM algorithm. Journal of the Royal Statistical Society, Series B, 44, 226-233.
    • (1982) Journal of the Royal Statistical Society, Series B , vol.44 , pp. 226-233
    • Louis, T.A.1
  • 29
    • 0000251971 scopus 로고
    • Maximum likelihood estimation via the ECM algorithm: A general framework
    • Meng, X. L., & Rubin, D. B. (1993). Maximum likelihood estimation via the ECM algorithm: A general framework. Biometrika, 80, 267-278.
    • (1993) Biometrika , vol.80 , pp. 267-278
    • Meng, X.L.1    Rubin, D.B.2
  • 30
    • 0030336223 scopus 로고    scopus 로고
    • Fitting full-information item factor models and an empirical investigation of bridge sampling
    • Meng, X. L., & Schilling, S. (1996). Fitting full-information item factor models and an empirical investigation of bridge sampling. Journal of American Statistical Association, 91, 1254-1267.
    • (1996) Journal of American Statistical Association , vol.91 , pp. 1254-1267
    • Meng, X.L.1    Schilling, S.2
  • 31
    • 21444451325 scopus 로고    scopus 로고
    • Simulating ratios of normalizing constants via a simple identity: A theoretical exploration
    • Meng, X. L., & Wong, W. H. (1996). Simulating ratios of normalizing constants via a simple identity: A theoretical exploration. Statistica Sinica, 6, 831-860.
    • (1996) Statistica Sinica , vol.6 , pp. 831-860
    • Meng, X.L.1    Wong, W.H.2
  • 34
    • 0002884680 scopus 로고
    • Bayesian model selection in structural equation models
    • K. A. Bollen & J. S. Long (Eds.), London: New Delhi
    • Raftery, A. E. (1993). Bayesian model selection in structural equation models. In K. A. Bollen & J. S. Long (Eds.), Testing structural equation models (pp. 163-180). London: New Delhi.
    • (1993) Testing Structural Equation Models , pp. 163-180
    • Raftery, A.E.1
  • 36
    • 0036012997 scopus 로고    scopus 로고
    • Publication bias and meta-analysis for 2 × 2 tables: An average Markov chain Monte Carlo em algorithm
    • Shi, J. Q., & Copas, J. (2002). Publication bias and meta-analysis for 2 × 2 tables: An average Markov chain Monte Carlo EM algorithm. Journal of the Royal Statistical Society, Series B, 64, 221-236.
    • (2002) Journal of the Royal Statistical Society, Series B , vol.64 , pp. 221-236
    • Shi, J.Q.1    Copas, J.2
  • 38
    • 27844516595 scopus 로고    scopus 로고
    • Bayesian analysis of structural equation models with nonlinear covariates and latent variables
    • Song, X. Y., & Lee, S. Y. (2005a). Bayesian analysis of structural equation models with nonlinear covariates and latent variables. Multivariate Behavioral Research, 40, 151-177.
    • (2005) Multivariate Behavioral Research , vol.40 , pp. 151-177
    • Song, X.Y.1    Lee, S.Y.2
  • 39
    • 27144553773 scopus 로고    scopus 로고
    • A multivariate probit latent variable model for analyzing dichotomous responses
    • Song, X. Y., & Lee, S. Y. (2005b). A multivariate probit latent variable model for analyzing dichotomous responses. Statistica Sinica, 15, 645-664.
    • (2005) Statistica Sinica , vol.15 , pp. 645-664
    • Song, X.Y.1    Lee, S.Y.2
  • 40
    • 84950758368 scopus 로고
    • The calculation of posterior distributions by data augmentation
    • Tanner, M. A., & Wong, W. H. (1987). The calculation of posterior distributions by data augmentation (with discussion). Journal of American Statistical Association, 82, 528-550.
    • (1987) Journal of American Statistical Association , vol.82 , pp. 528-550
    • Tanner, M.A.1    Wong, W.H.2
  • 41
    • 84950432017 scopus 로고
    • A Monte Carlo implementation of the em algorithm and the poor man's data augmentation algorithm
    • Wei, G. C. G., & Tanner, M. A. (1990). A Monte Carlo implementation of the EM algorithm and the poor man's data augmentation algorithm. Journal of the American Statistical Association, 85, 699-704.
    • (1990) Journal of the American Statistical Association , vol.85 , pp. 699-704
    • Wei, G.C.G.1    Tanner, M.A.2
  • 42
    • 0003830430 scopus 로고
    • Ann Arbor, MI: Institute for Social Research and Interuniversity Consortium for Political and Social Research.
    • World Values Survey, 1981-1984 and 1990-1993 (ICPSR version). (1994). Ann Arbor, MI: Institute for Social Research and Interuniversity Consortium for Political and Social Research.
    • (1994) World Values Survey, 1981-1984 and 1990-1993 (ICPSR Version)
  • 43
    • 25444473930 scopus 로고    scopus 로고
    • Fit indices versus test statistics
    • Yuan, K. H. (2005). Fit indices versus test statistics. Multivariate Behavioral Research, 40, 115-148.
    • (2005) Multivariate Behavioral Research , vol.40 , pp. 115-148
    • Yuan, K.H.1


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