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Parametric models for response‐biased sampling

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  • Kani Chen

Abstract

Suppose that subjects in a population follow the model f (y*x*;θ) where y* denotes a response, x* denotes a vector of covariates and θ is the parameter to be estimated. We consider response‐biased sampling, in which a subject is observed with a probability which is a function of its response. Such response‐biased sampling frequently occurs in econometrics, epidemiology and survey sampling. The semiparametric maximum likelihood estimate of θ is derived, along with its asymptotic normality, efficiency and variance estimates. The estimate proposed can be used as a maximum partial likelihood estimate in stratified response‐selective sampling. Some computation algorithms are also provided.

Suggested Citation

  • Kani Chen, 2001. "Parametric models for response‐biased sampling," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(4), pages 775-789.
    • Handle: RePEc:bla:jorssb:v:63:y:2001:i:4:p:775-789
    DOI: 10.1111/1467-9868.00312
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    Cited by:

    1. Xuerong Chen & Guoqing Diao & Jing Qin, 2020. "Pseudo likelihood‐based estimation and testing of missingness mechanism function in nonignorable missing data problems," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 47(4), pages 1377-1400, December.
    2. Ping Wang & Lu Lin, 2023. "Conditional characteristic feature screening for massive imbalanced data," Statistical Papers, Springer, vol. 64(3), pages 807-834, June.
    3. Sung Jae Jun & Sokbae Lee, 2020. "Causal Inference under Outcome-Based Sampling with Monotonicity Assumptions," Papers 2004.08318, arXiv.org, revised Oct 2023.
    4. Lukáš Lafférs & Bernhard Schmidpeter, 2021. "Early child development and parents' labor supply," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(2), pages 190-208, March.
    5. Sung Jae Jun & Sokbae (Simon) Lee, 2020. "Causal inference in case-control studies," CeMMAP working papers CWP19/20, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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