Structural Equation Models

The Oxford Handbook of Political Methodology

Volumn , Issue , 2008, Pages

  Bollen, Kenneth A ^a   Rabe Hesketh, Sophia ^b,c   Skrondal, Anders ^d  

^a UNIVERSITY OF NORTH CAROLINA   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF LONDON   (United Kingdom)

^d LONDON SCHOOL OF ECONOMICS   (United Kingdom)

Author keywords

Factor analysis; Graphical models; Latent variables; Observed variables; Structural equation models

Indexed keywords

EID: 84924033160     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1093/oxfordhb/9780199286546.003.0018     Document Type: Chapter

References (56)

1. ARMINGER, G., and SCHOENBERG, R. 1989. Pseudo maximum likelihood estimation and a test for misspecification in mean and covariance structure models. Psychometrika, 54: 409-25.
2. BARNES, S. H., KAASE, M., ALLERBECK, K. R., FARAH, B. J., HEUNKS, F., INGLEHART, R., JENNINGS, M. K., KLINGEMANN, H. D., MARSH, H., and ROSENMAYR, L. 1979. Political Action: Mass Participation in Five Western Democracies. Beverly Hills, Calif.: Sage.
3. BARTHOLOMEW, D. J. 1987. Latent Variable Models and Factor Analysis. Oxford: Oxford University Press.
4. BOLLEN, K. A. 1989. Structural Equations with Latent Variables. New York: John Wiley.
5. BOLLEN, K. A. 1996. An alternative two stage least squares (2SLS) estimator for latent variable equations. Psychometrika, 61: 109-21.
6. BOLLEN, K. A. 2001. Two-stage least squares and latent variable models: simultaneous estimation and robustness to misspecifications. Pp. 119-38, in Structural Equation Modeling: Present and Future, ed. R. Cudeck, S. du Toit, and D. Sörbom. Lincolnwood, Ill.: Scientific Software.
7. BOLLEN, K. A. 2002. Latent variables in psychology and the social sciences. Annual Review of Psychology, 53: 605-34.
8. BOLLEN, K. A., and ARMINGER, G. 1991. Observational residuals in factor analysis. Sociological Methodology, 21: 235-62.
9. BOLLEN, K. A., and BAUER, D. J. 2004. Automating the selection of model-implied instrumental variables. Sociological Methods and Research, 32: 425-52.
10. BOLLEN, K. A., and LONG, J. S., (eds.) 1993. Testing Structural Equation Models. Newbury Park, Calif.: Sage.
11. BOLLEN, K. A., and STINE, R. A. 1990. Direct and indirect effects: classical and bootstrap estimates of variability. Sociological Methodology, 20: 115-40.
12. BOLLEN, K. A., and STINE, R. A. 1993. Bootstrapping goodness-of-fit measures in structural equation models. Pp. 111-35 in Testing Structural Equation Models, ed. A. Kenneth and J. S. Long. Newbury Park, Calif.: Sage.
13. BOX-STEFFENSMEIER, J. M., and JONES, B. S. 2004. Event History Modeling: A Guide to Social Statistics. Cambridge: Cambridge University Press.
14. BROWNE, M. W. 1984. Asymptotically distribution-free methods for the analysis of covariance structures. British Journal of Mathematical and Statistical Psychology, 37: 62-83.
15. CADIGAN, N. G. 1995. Local influence in structural equations models. Structural Equation Modeling, 2: 13-30.
16. CAMPBELL, A., GURIN, G., and MILLER, W. E. 1954. The Voter Decides. Evanston, Ill.: Row Peterson.
17. COSTNER, H. L., and SCHOENBERG, R. 1973. Diagnosing indicator ills in multiple indicator models. Pp. 167-200 in Structural Equation Models in the Social Sciences, ed. A. S. Goldberger and O. D. Duncan. New York: Seminar Press.
18. DAVIS, W. R. 1993. The FC1 rule of identification for confirmatory factor analysis: a general sufficient condition. Sociological Methods and Research, 21: 403-37.
19. FISHER, F. M. 1966. The Identification Problem in Econometrics. New York: McGraw-Hill.
20. GOLDSTEIN, H. 1987. Multilevel covariance component models. Biometrika, 74: 430-1.
21. GOLDSTEIN, H. 2003. Multilevel Statistical Models, 3rd edn. London: Arnold.
22. HÄGGLUND, G. 1982. Factor analysis by instrumental variables. Psychometrika, 47: 209-22.
23. HOX, J. 2002. Multilevel Analysis: Techniques and Applications. Mahwah, NJ: Erlbaum.
24. HU, L., and BENTLER, P. M. 1998. Fit indices in covariance structure modeling: sensitivity to underparameterization model misspecification. Psychological Methods, 3: 424-53.
25. JÖRESKOG, K. G. 1969. A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34: 183-202.
26. JÖRESKOG, K. G. 1973. A general method for estimating a linear structural equation. Pp. 85-112 in Structural Equation Models in the Social Sciences, ed. A. S. Golderberger and O. D. Duncan, New York: Seminar Press.
27. JÖRESKOG, K. G. 1983. Factor analysis as an error-in-variables model. Pp. 185-96 in Principles of Modern Psychological Measurement, ed. H. Wainer and S. Messick. Hillsdale, NJ: Lawrence Erlbaum.
28. JÖRESKOG, K. G., and SÖRBOM, D. 1993. LISREL 8. Mooreseville, Ind.: Scientific Software.
29. KING, G. 1988. Statistical models for political science event counts. American Journal of Political Science, 32: 838-63.
30. LEE, S.-Y., and SONG, X.-Y. 2003. Bayesian analysis of structural equation models with dichotomous variables. Statistics in Medicine, 22: 3073-88.
31. LONGFORD, N. T. 1993. Random Coefficient Models. Oxford: Oxford University Press.
32. LONGFORD, N. T., and MUTHÉN, B. O. 1992. Factor analysis for clustered observations. Psychometrika, 57: 581-97.
33. MAC CALLUM, R. 1986. Specification searcher in covariance structure modeling. Psychological Bulletin, 100: 107-20.
34. MC CULLOCH, C. E. 1997. Maximum likelihood algorithms for generalized linear mixed models. Journal of the American Statistical Association, 92: 162-70.
35. MADANSKY, A. 1964. Instrumental variables in factor analysis. Psychometrika, 29: 105-13.
36. MELLENBERGH, G. J. 1994. Generalized linear item response theory. Psychological Bulletin, 115: 300-7.
37. MILLER, W. E., MILLER, A. H., and SCHNEIDER, E. J. 1980. American National Election Studies Data Source-Book: 1952-1978. Cambridge, Mass.: Harvard University Press.
38. MUTHÉN, B. O. 1978. Contributions to factor analysis of dichotomous variables. Psychometrika, 43: 551-60.
39. MUTHÉN, B. O. 1989. Latent variable modeling in heterogeneous populations. Psychometrika, 54: 557-85.
40. MUTHÉN, B. O. 1994. Multilevel covariance structure analysis. Sociological Methods and Research, 22: 376-98.
41. MUTHÉN, B. O., and SATORRA, A. 1996. Technical aspects of Muthén's LISCOMP approach to estimation of latent variable relations with a comprehensive measurement model. Psychometrika, 60: 489-503.
42. MUTHÉN, L. K., and MUTHÉN, B. O. 2004. Mplus User's Guide, 3rd edn. Los Angeles: Muthén and Muthén.
43. POON, W.-Y., and LEE, S.-Y. 1992. Maximum likelihood and generalized least squares analyses of two-level structural equation models. Statistics and Probability Letters, 14: 25-30.
44. RABE-HESKETH, S., and SKRONDAL, A. 2001. Parameterization of multivariate random effects models for categorical data. Biometrics, 57: 1256-64.
45. RABE-HESKETH, S., and SKRONDAL, A. 2008. Multilevel and Longitudinal Modeling using Stata. College Station, Tex.: Stata Press.
46. RABE-HESKETH, S., SKRONDAL, A., and PICKLES, A. 2004. Generalized multilevel structural equation modeling. Psy-chometrika, 69: 167-90.
47. RABE-HESKETH, S., SKRONDAL, A., and PICKLES, A. 2005. Maximum likelihood estimation of limited and discrete dependent variable models with nested random effects. Journal of Econometrics, 128: 301-23.
48. RUBIN, D. B. 1987. Multiple Imputation for Nonresponse in Surveys. New York: Wiley.
49. SAMEJIMA, F. 1969. Estimation of Latent Trait Ability Using a Response Pattern of Graded Scores. Bowling Green, Ohio: Psychometric Society.
50. SATORRA, A. 1990. Robustness issues in structural equation modeling: a review of recent developments. Quality and Quantity, 24: 367-86.
51. SATORRA, A., and BENTLER, P. M. 1994. Corrections to test statistics and standard errors in covariance structure analysis. Pp. 399-419 in Latent Variables Analysis: Applications for Development Research, ed. A. von Eye and C. C. Clogg. Newbury Park, Calif.: Sage.
52. SKRONDAL, A., and RABE-HESKETH, S. 2003. Multilevel logistic regression for polytomous data and rankings. Psychometrika, 68: 267-87.
53. SKRONDAL, A., and RABE-HESKETH, S. 2004. Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models. Boca Raton, Fla.: Chapman and Hall/CRC.
54. SPIEGELHALTER, D. J., THOMAS, A., BEST, N. G., and GILKS, W. R. 1996. BUGS 0.5 Bayesian Analysis using Gibbs Sampling. Manual (version ii). Cambridge: MRC-Biostatistics Unit; available from .
55. TAKANE, Y., and DE LEEUW, J. 1987. On the relationship between item response theory and factor analysis of discretized variables. Psychometrika, 52: 393-408.
56. WRIGHT, S. 1918. On the nature of size factors. Genetics, 3: 367-74.