Simultaneous estimation and inference for multiple response variables

References

• Alexander, C. S., and R. Markowitz. 1986. Maternal employment and use of pediatric clinic services. Medical Care 24:134–47.
   PubMed Web of Science ®Google Scholar
• Altonji, J. G., and L. M. Segal. 1996. Small-sample bias in GMM estimation of covariance structures. Journal of Business and Economic Statistics 14:353–66.
   Web of Science ®Google Scholar
• Andrews, D. W. 1999. Consistent moment selection procedures for generalized method of moments estimation. Econometrica 67:543–63.
   Web of Science ®Google Scholar
• Arnold, S. F. 1981. The theory of linear models and multivariate analysis. New York, NY: John Wiley and Sons.
   Google Scholar
• Breiman, L., and J. H. Friedman. 1997. Predicting multivariate responses in multiple linear regression. Journal of the Royal Statistical Society Series B 59:3–54.
   Google Scholar
• Catalano, P. J., and L. M. Ryan. 1992. Bivariate latent variable models for clustered discrete and continuous outcomes. Journal of the American Statistical Association 87:651–58.
   Web of Science ®Google Scholar
• Chen, L., and J. Huang. 2012. Sparse reduced-rank regression for simultaneous dimension reduction and variable selection. Journal of American Statistical Association 107:1533–45.
   Web of Science ®Google Scholar
• Chen, J., and Y. Huang. 2013. Finite-sample properties of the adjusted empirical likelihood. Journal of Nonparametric Statistics 25:147–59.
   Web of Science ®Google Scholar
• Cho, H., and A. Qu. 2015. Efficient estimation for longitudinal data by combining large-dimensional moment conditions. Electronic Journal of Statistics 9:1315–34.
   Web of Science ®Google Scholar
• Demirtas, H., A. Amatya, and B. Doganay. 2014. BinNor: An R package for concurrent generation of binary and normal data. Communications in Statistics-Simulation and Computation 43:569–79.
   Web of Science ®Google Scholar
• DiCiccio, T., P. Hall, and J. Romano. 1991. Empirical likelihood is Bartlett-correctable. The Annals of Statistics 19 1053–61.
   Web of Science ®Google Scholar
• DiTraglia, F. J. 2016. Using invalid instruments on purpose: Focused moment selection and averaging for GMM. Journal of Econometrics 195:187–208.
   Web of Science ®Google Scholar
• Donald, S. G., G. W. Imbens, and W. K. Newey. 2009. Choosing instrumental variables in conditional moment restriction models. Journal of Econometrics 152:28–36.
   Web of Science ®Google Scholar
• Fitzmaurice, G. M., and N. M. Laird. 1997. Regression models for mixed discrete and continuous responses with potentially missing values. Biometrics 53:110–22.
   PubMed Web of Science ®Google Scholar
• Hansen, L. P. 1982. Large sample properties of generalized method of moments estimators. Econometrica 50:1029–54.
   Web of Science ®Google Scholar
• Horowitz, J. L. 1998. Bootstrap methods for covariance structures. Journal of Human Resources 33:39–61.
   Web of Science ®Google Scholar
• Imbens, G. W. 2002. Generalized method of moments and empirical likelihood. Journal of Business and Economic Statistics 20:493–506.
   Web of Science ®Google Scholar
• Leisch, F., A. Weingessel, and K. Hornik. 2011. bindata: Generation of artificial binary data. R package version 0.9-19.
   Google Scholar
• Liang, K. Y., and S. L. Zeger. 1986. Longitudinal data analysis using generalised linear models. Biometrika 73:12–22.
   Web of Science ®Google Scholar
• Liao, Z. 2013. Adaptive GMM shrinkage estimation with consistent moment selection. Econometric Theory 29:857–904.
   Web of Science ®Google Scholar
• Lee, W., and Y. Liu. 2012. Simultaneous multiple response regression and inverse covariance matrix estimation via penalized Gaussian maximum likelihood. Journal of Multivariate Analysis 111:241–55.
   PubMed Web of Science ®Google Scholar
• Newey, W. K., and R. J. Smith. 2004. Higher order properties of GMM and generalized empirical likelihood estimators. Econometrica 72:219–55.
   Web of Science ®Google Scholar
• Okui, R. 2009. The optimal choice of moments in dynamic panel data models. Journal of Econometrics 151:1–16.
   Web of Science ®Google Scholar
• Owen, A. B. 1988. Empirical likelihood ratio confidence intervals for a single functional. Biometrika 75:237–49.
   Web of Science ®Google Scholar
• Prentice, R. L., and L. P. Zhao. 1991. Estimating equations for parameters in means and covariances of multivariate discrete and continuous responses. Biometrics 47:825–39.
   PubMed Web of Science ®Google Scholar
• Qin, J., and J. Lawless. 1994. Empirical likelihood and general estimating equations. The Annals of Statistics 22:300–25.
   Web of Science ®Google Scholar
• Qu, A., and B. G. Lindsay, 2003. Building adaptive estimating equations when inverse of covariance estimation is difficult. Journal of the Royal Statistical Society: Series B 65:127–42.
   Google Scholar
• Qu, A., B. G. Lindsay, and B. Li. 2000. Improving generalised estimating equations using quadratic inference functions. Biometrika 87:823–36.
   Web of Science ®Google Scholar
• Ripley, B., B. Venables, D. M. Bates, K. Hornik, A. Gebhardt, and D. Firth. 2018. MASS: Support functions and datasets. R package version 7. 3–49.
   Google Scholar
• Rothman, A. J., E. Levina, and J. Zhu. 2010. Sparse multivariate regression with covariance estimation. Journal of Computational and Graphical Statistics 19:947–62.
   PubMed Web of Science ®Google Scholar
• Sammel, M. D., L. M. Ryan, and J. M. Legler. 1997. Latent variable models for mixed discrete and continuous outcomes. Journal of the Royal Statistical Society Series B 59:667–78.
   Google Scholar
• Teixeira-Pinto, A., and S. L. Normand. 2009. Correlated bivariate continuous and binary outcomes: Issues and applications. Statistics in Medicine 28:1753–73.
   PubMed Web of Science ®Google Scholar
• Wang, J. 2015. Joint estimation of sparse multivariate regression and conditional graphical models. Statistica Sinica 25:831–51.
   Web of Science ®Google Scholar
• Westgate, PM. 2012. A bias-corrected covariance estimate for improved inference with quadratic inference functions. Statistics in Medicine 31:4003–22.
   PubMed Web of Science ®Google Scholar
• Westgate, PM. 2013. A bias-corrected covariance estimator for improved inference when using an unstructured correlation with quadratic inference functions. Statistics and Probability Letters 83:1553–8.
   Web of Science ®Google Scholar
• Yuan, M., A. Ekici, Z. Lu, and R. Monteiro. 2007. Dimension reduction and coefficient estimation in multivariate linear regression. Journal of the Royal Statistical Society Series B 69:329–46.
   Google Scholar
• Zhao, L. P., R. L. Prentice, and S. G. Self. 1992. Multivariate mean parameter estimation by using a partly exponential model. Journal of the Royal Statistical Society Series B 54:805–11.
   Google Scholar