References: |
Adams, R. J., Wilson, M., Wang, W. C. (1997a). The multidimensional random coefficients multinomial logit model. Applied Psychological Measurment 21:1–23. Adams, R. J., Wilson, M., Wu, M. (1997b). Multilevel item response models: an approach to errors in variables regression. Journal of Educational and Behavioral Statistics 22:47–76. Anderson, N. E., Bankroft, T. A. (1952). Statistical Theory in Research. New York: McGraw- Hill. Baker, F. B., Kim, S. H. (2004). Item Response Theory, Parameter Estimation Tehniques. Marcel Dekker, Inc. Bergner, M., Bobbil, R. A., Pollard, W. G., Martin, D. P., Gilson, B. S. (1976). The sickness impact profile: validation of a health status measure. Medical Care 14:56–67. Breslow, N. E., Clayton, D. G. (1993). Approximate inference in generalized linear mixed models. Journal of the American Statistical Association 88:9–25. Breslow, N. E., Lin, X. (1995). Bias correction in generalized linear models with a single component of dispersion. Biometrika 82:81–92. De Boeck, P., Wilson, M. (2004). Explanatory Item Response Theory. Springer. Diggle, P. J., Liang, K. Y., Zeger, S. L. (1994). Analysis of Longitudinal Data. Oxford: Oxford University Press. Embretson, S. E. (1991). A multidimensional latent trait model for measuring learning and change. Psychometrika 56:491–515. Feddag, M. L., Mesbah, M. (2005). Generalized estimating equations for longitudinal mixed Rasch model. Journal of Statistical Planning and Inference 129:159–179. Feddag, M. L., Mesbah, M. (2006). Approximate estimation in generalized linear mixed models with applications to the Rasch model. Computer and Mathematics with Applications 51:269–278. Feddag, M. L., Grama, I., Mesbah, M. (2003). Generalized estimating equations for mixed logistic models. Communications in Statistics: Theory and Methods 32(4):851–874. Fischer, G. H., Molenaar, I. W. (1995). Rasch Models Foundations, Recent Developments and Applications. Springer-Verlag. Gilks, W. R., Wild, P. (1992). Adaptative rejection sampling for Gibbs sampling. Applied Statistics 4:337–348. Hedeker, D., Gibbons, R. D. (1994). A random effects ordinal regression model for multilivel analysis. Biometrics 50:933–944. Hoijtink, H. (1995). Linear and repeated measures models for the person parameter. In: Fischer, G. H., Molenaar, I. W., eds. Rasch Models Foundations, Recents Developments and Applications. Springer-Verlag, pp. 203–214. Liang, K. Y., Zeger, S. L. (1986). Longitudinal data analysis using generalized linear models. Biometrika 73:13–22. McCullagh, P., Nelder, J. A. (1989). Generalized Linear Models. 2nd ed. London: Chapman and Hall. Pan, W. (2001). Akaike’s information criterion bias in generalized estimating equations. Biometrics 57:120–125. Pinheiro, J. C., Bates, D. M. (1995). Approximation to the log-likelihood function in the nonlinear mixed effects models. Journal of Computational and Graphical Statistics 4:12–35. Prentice, R. L. (1988). Correlated binary regression with covariates specific to each binary observation. Biometrics 44:1033–1048. Prentice, R. L., Zhao, L. P. (1991). Estimating equation for parameters in means and covariances of multivariate discrete and continuous responses. Biometrics 47:825–839. Rigdon, S. E., Tsutakawa, R. K. (1983). Parameter estimation in latent trait models. Psychometrika 48:567–574. Rijmen, F., De Boeck, P., Van Der Maas, H. L. J. (2005). An IRT model with parameterdriven process for change. Psychometrika 70:651–669. Sutradhar, B. C., Rao, R. P. (2001). On marginal quasi-likelihood inference in generalized linear mixed models. Journal of Multivariate Analysis 76:1–34. te Marvelde, J. M., Glass, C. A. W., Landeghem, G. V., Damme, J. V. (2006). Application of multidimensional item response theory models to longitudinal data. Educational and Psychological Measurement 66:5–34. Wakefield, J. C., Smith, A. F. M., Racine-Poon, A., Gelfand, A. E. (1994). Bayesian analysis of linear and non-linear population models by using the Gibbs sampler. Applied Statistics 43:201–221. Wedderburn, R. W. M. (1974). Quasi-likelihood function, generalized linear models and the Gauss–Newton method. Biometrika 48:439–447. Zhao, L. P., Prentice, R. L. (1990). Correlated binary regression using a quadratic exponential model. Biometrika 77:642-648. Zeger, S. L., Karim, M. R. (1991). Generalized linear models with random effects: a Gibbs sampling approach. Journal of the American Statistical Association 86:79–86. Zeger, S. L., Liang, K. Y., Albert, P. S. (1988). Models for longitudinal data: a generalized estimating equation approach. Biometrics 44:1049–1060. |