References
- Kim, J. K., & Yu, C. L. (2011). A semiparametric estimation of mean functionals with nonignorable missing data. Journal of the American Statistical Association, 106, 157–165. doi: 10.1198/jasa.2011.tm10104
- Lee, S. Y., & Tang, N. S. (2006). Bayesian analysis of nonlinear structural equation models with nonignorable missing data. Psychometrika, 71, 541–564. doi: 10.1007/s11336-006-1177-1
- Qin, J., Leung, D., & Shao, J. (2002). Estimation with survey data under non-ignorable nonresponse or informative sampling. Journal of American Statistical Association, 97, 93–200. doi: 10.1198/016214502753479338
- Shao, J., & Wang, L. (2016). Semiparametric inverse propensity weighting for nonignorable missing data. Biometrika, 103, 175–187. doi: 10.1093/biomet/asv071
- Wang, S., Shao, J., & Kim, J. (2014). An instrumental variable approach for identification and estimation with nonignorable nonresponse. Statistica Sinica, 24, 1097–1116.
- Zhao, J., & Shao, J. (2015). Semiparametric pseudo likelihoods in generalized linear models with nonignorable missing data. Journal of American Statistical Association, 110, 1577–1590. doi: 10.1080/01621459.2014.983234
- Zhao, J., & Shao, J. (2017). Approximate conditional likelihood for generalized linear models with general missing data mechanism. Journal of System Science and Complexity, 30, 139–153. doi: 10.1007/s11424-017-6188-3