Regression Estimation for Longitudinal Data with Nonignorable Intermittent Nonresponse and Dropout

Ai, C., Linton, O., Zhang, Z.: A simple and efficient estimation method for models with nonignorable missing data. Statistica Sinica, preprint. (2018). https://doi.org/10.5705/ss.202018.0107

Diggle, P.J.: The analysis of longitudinal data. J. Am. Stat. Assoc. 90, 1231–1232 (2002)

Fang, F., Shao, J.: Model selection with nonignorable nonresponse. Biometrika 103, 861–874 (2016)

Fitzmaurice, G.M., Molenberghs, G., Lipsitz, S.R.: Regression models for longitudinal binary responses with informative dropouts. J. Roy. Stat. Soc. B 57, 691–704 (1995)

Han, P.S., Song, P.X.K., Wang, L.: Achieving semiparametric efficiency bound in longitudinal data analysis with dropouts. J. Multivar. Anal. 135, 59–70 (2015)

Hansen, L.: Large sample properties of generalized method of moments estimators. Econometrica 50, 1029–1054 (1982)

Henry, K., Erice, A., Tierney, C., Balfour, H.H.J., Fischl, M.A., Kmack, A., Liou, S.H., Kenton, A., Hirsch, M.S., Phair, J., Martinez, A., Kahn, J.O. and for the AIDS Clinical Trial Group 193A Study Team: A randomized, controlled, double-blind study comparing the survival benefit of four different reverse transcriptase inhibitor therapies (three-drug, two-drug, and alternating drug) for the treatment of advanced AIDS. Journal of Acquired Immune Deficiency Syndromes and Human Retrovirology 19, 339–349 (1998)

Kim, J.K., Yu, C.L.: A semiparametric estimation of mean functionals with nonignorable missing data. J Am Stat Assoc 106, 157–165 (2011)

Little, R.J.A., Rubin, D.B.: Statistical Analysis with MissingData, 2nd edn. Wiley, New York (2002)

Miao, W., Tchetgen, E.: On varieties of doubly robust estimators under missingness not at random with a shadow variable. Biometrika 103, 475–482 (2016)

Morikawa, K., Kim, J.K., Kano, Y.: Semiparametric maximum likelihood estimation with data missing not at random. Can. J. Stat. 45, 393–409 (2017)

Newey, W., Mcfadden, D.: Large Sample Estimation and Hypothesis Testing. Springer, New York (1994)

Robins, et al.: Estimation of regression coefficients when some regressors are not always observed. J. Am. Stat. Assoc. 89: 846–866 (1994)

Robins, J.M., Ritov, Y.: Toward a curse of dimensionality appropriate (CODA) asymptotic theory for semi-parametric models. Stat. Med. 16, 285–319 (1997)

Seaman, S.R., Farewell, D., White, I.R.: Linear increments with non-monotone missing data and measurement error. Scand. J. Stat. 43, 996–1018 (2016)

Shao, J., Wang, L.: Semiparametric inverse propensity weighting for nonignorable missing data. Biometrika 103, 175–187 (2016)

Tsonaka, R., Rizopoulos, D., Verbeke, G., Lesaffre, E.: Nonignorable models for intermittently missing categorical longitudinal responses. Biometrics 66, 834–844 (2010)

Vansteelandt, S., Rotnitzky, A., Robins, J.: Estimation of regression models for the mean of repeated outcomes under nonignorable nonmonotone nonresponse. Biometrika 94, 841–860 (2007)

Wang, S., Shao, J., Kim, J.K.: An instrumental variable approach for identifcation and estimation with nonignorable nonresponse. Stat. Sin. 24, 1097–1116 (2014)

Wang, L., Shao, J., Fang, F.: Propensity model selection with nonignorable nonresponse and instrument variable. Stat. Sinica (2018). https://doi.org/10.5705/ss.202019.0025

Wang, L., Qi, C.C., Shao, J.: Model-assisted regression estimators for longitudinal data with nonignorable dropout. Int. Stat. Rev. 87(S1), S121–S138 (2019)

Xu, J., Shao, J., Palta, M., Wang, L.: Imputation for longitudinal data with last-value-dependent non-monotone missing values. Surv. Methodol. 34, 153–162 (2008)

Zhao, J., Shao, J.: Semiparametric pseudo likelihoods in generalized linear models with nonignorable missing data. J. Am. Stat. Assoc. 110, 1577–1590 (2015)

Zhao, P., Tang, N., Qu, A., Jiang, D.: Semiparametric estimating equations inference with nonignorable missing data. Stat. Sin. 27, 89–113 (2017)

Zhao, P., Wang, L., Shao, J.: Analysis of longitudinal data under nonignorable nonmonotone nonresponse. Stat. Interface 11, 265–279 (2018)

Zhou, M., Kim, J.K.: An efficient method of estimation for longitudinal surveys with monotone missing data. Biometrika 99, 631–648 (2012)