A propensity score adjustment method for longitudinal time series models under nonignorable nonresponse-Reference-Cited by-同舟云学术

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A propensity score adjustment method for longitudinal time series models under nonignorable nonresponse

Published:2021-09-14 Issue:1 Volume:63 Page:317-342
ISSN:0932-5026
Container-title:Statistical Papers
language:en
Short-container-title:Stat Papers

Author:

Liu Zhan^ORCID,Yau Chun Yip

Funder

hksar-rgc-grf

National Office for Philosophy and Social Sciences

Publisher

Springer Science and Business Media LLC

Subject

Statistics, Probability and Uncertainty,Statistics and Probability

Link

https://link.springer.com/content/pdf/10.1007/s00362-021-01261-0.pdf

Reference41 articles.

1. Bahari F, Parsi S, Ganjali M (2019) Empirical likelihood inference in general linear model with missing values in response and covariates by MNAR mechanism. Stat Pap. https://doi.org/10.1007/s00362-019-01103-0

2. Bickel PJ, Doksum KA (1977) Mathematical statistics: basic ideas and selected topics. Holden-Day, San Francisco

3. Binder DA (1983) On the variances of asymptotically normal estimators from complex surveys. Int Stat Rev 51(3):279–292

4. Brockwell PJ, Davis RA (1991) Time series: theory and methods, 2nd edn. Springer, New York

5. Davis RA, Yau CY (2011) Comments on pairwise likelihood in time series models. Stat Sin 21(1):255–277

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