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Propensity score adjustment with several follow-ups

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  • Jae Kwang Kim
  • Jongho Im

Abstract

Propensity score weighting adjustment is commonly used to handle unit nonresponse. When the response mechanism is nonignorable in the sense that the response probability depends directly on the study variable, a follow-up sample is commonly used to obtain an unbiased estimator using the framework of two-phase sampling, where the follow-up sample is assumed to respond completely. In practice, the follow-up sample is also subject to missingness. We consider propensity score weighting adjustment for nonignorable nonresponse when there are several follow-ups and the final follow-up sample is also subject to missingness. We propose a method-of-moments estimator for estimating parameters in the response probability. The proposed method can be implemented using the generalized method of moments and a consistent variance estimate can be obtained relatively easily. A limited simulation study shows the robustness of the proposed method. The proposed methods are applied to a Korean household survey of employment.

Suggested Citation

  • Jae Kwang Kim & Jongho Im, 2014. "Propensity score adjustment with several follow-ups," Biometrika, Biometrika Trust, vol. 101(2), pages 439-448.
    • Handle: RePEc:oup:biomet:v:101:y:2014:i:2:p:439-448.
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    File URL: http://hdl.handle.net/10.1093/biomet/asu003
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    Cited by:

    1. Zhong, Ping-Shou & Chen, Sixia, 2014. "Jackknife empirical likelihood inference with regression imputation and survey data," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 193-205.
    2. Heng Chen & Geoffrey Dunbar & Q. Rallye Shen, 2020. "The Mode is the Message: Using Predata as Exclusion Restrictions to Evaluate Survey Design," Advances in Econometrics, in: Essays in Honor of Cheng Hsiao, volume 41, pages 341-357, Emerald Group Publishing Limited.
    3. Zhong Guan & Jing Qin, 2017. "Empirical likelihood method for non-ignorable missing data problems," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 23(1), pages 113-135, January.
    4. Pender, John & Kuhns, Maria & Yu, Cindy & Larson, Janice & Huck, Shirley, 2023. "Linkages Between Rural Community Capitals and Healthcare Provision: A Survey of Small Rural Towns in Three U.S. Regions," USDA Miscellaneous 333533, United States Department of Agriculture.
    5. Zhan Liu & Chun Yip Yau, 2022. "A propensity score adjustment method for longitudinal time series models under nonignorable nonresponse," Statistical Papers, Springer, vol. 63(1), pages 317-342, February.

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