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Identification of graphical models for nonignorable nonresponse of binary outcomes in longitudinal studies

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  • Ma, Wen-Qing
  • Geng, Zhi
  • Hu, Yong-Hua

Abstract

In this paper, we use directed acyclic graphs (DAGs) with temporal structure to describe models of nonignorable nonresponse mechanisms for binary outcomes in longitudinal studies, and we discuss identification of these models under an assumption that the sequence of variables has the first-order Markov dependence, that is, the future variables are independent of the past variables conditional on the present variables. We give a stepwise approach for checking identifiability of DAG models. For an unidentifiable model, we propose adding completely observed variables such that this model becomes identifiable.

Suggested Citation

  • Ma, Wen-Qing & Geng, Zhi & Hu, Yong-Hua, 2003. "Identification of graphical models for nonignorable nonresponse of binary outcomes in longitudinal studies," Journal of Multivariate Analysis, Elsevier, vol. 87(1), pages 24-45, October.
    • Handle: RePEc:eee:jmvana:v:87:y:2003:i:1:p:24-45
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    References listed on IDEAS

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    1. Glonek, G. F. V., 1999. "On identifiability in models for incomplete binary data," Statistics & Probability Letters, Elsevier, vol. 41(2), pages 191-197, January.
    2. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-591, May.
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    Cited by:

    1. Bindele, Huybrechts F. & Nguelifack, Brice M., 2019. "Generalized signed-rank estimation for regression models with non-ignorable missing responses," Computational Statistics & Data Analysis, Elsevier, vol. 139(C), pages 14-33.
    2. Hua Chen & Zhi Geng & Xiao-Hua Zhou, 2009. "Rejoinder," Biometrics, The International Biometric Society, vol. 65(3), pages 689-691, September.
    3. Yi He & Linzhi Zheng & Peng Luo, 2023. "Treatment Benefit and Treatment Harm Rates with Nonignorable Missing Covariate, Endpoint, or Treatment," Mathematics, MDPI, vol. 11(21), pages 1-18, October.
    4. Atanu Bhattacharjee, 2020. "Estimation of Treatment Effect with Missing Observations for Three Arms and Three Periods Crossover Clinical Trials," Annals of Data Science, Springer, vol. 7(3), pages 447-460, September.
    5. Yilin Li & Wang Miao & Ilya Shpitser & Eric J. Tchetgen Tchetgen, 2023. "A self‐censoring model for multivariate nonignorable nonmonotone missing data," Biometrics, The International Biometric Society, vol. 79(4), pages 3203-3214, December.

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