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Nested exposure case-control sampling: a sampling scheme to analyze rare time-dependent exposures

Author

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  • Jan Feifel

    (Ulm University)

  • Madlen Gebauer

    (Ulm University)

  • Martin Schumacher

    (University Medical Center Freiburg)

  • Jan Beyersmann

    (Ulm University)

Abstract

For large cohort studies with rare outcomes, the nested case-control design only requires data collection of small subsets of the individuals at risk. These are typically randomly sampled at the observed event times and a weighted, stratified analysis takes over the role of the full cohort analysis. Motivated by observational studies on the impact of hospital-acquired infection on hospital stay outcome, we are interested in situations, where not necessarily the outcome is rare, but time-dependent exposure such as the occurrence of an adverse event or disease progression is. Using the counting process formulation of general nested case-control designs, we propose three sampling schemes where not all commonly observed outcomes need to be included in the analysis. Rather, inclusion probabilities may be time-dependent and may even depend on the past sampling and exposure history. A bootstrap analysis of a full cohort data set from hospital epidemiology allows us to investigate the practical utility of the proposed sampling schemes in comparison to a full cohort analysis and a too simple application of the nested case-control design, if the outcome is not rare.

Suggested Citation

  • Jan Feifel & Madlen Gebauer & Martin Schumacher & Jan Beyersmann, 2020. "Nested exposure case-control sampling: a sampling scheme to analyze rare time-dependent exposures," Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, Springer, vol. 26(1), pages 21-44, January.
    • Handle: RePEc:spr:lifeda:v:26:y:2020:i:1:d:10.1007_s10985-018-9453-4
    DOI: 10.1007/s10985-018-9453-4
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    References listed on IDEAS

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    1. Norman E. Breslow & Jon A. Wellner, 2007. "Weighted Likelihood for Semiparametric Models and Two‐phase Stratified Samples, with Application to Cox Regression," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 34(1), pages 86-102, March.
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    Cited by:

    1. J. Feifel & D. Dobler, 2021. "Dynamic inference in general nested case‐control designs," Biometrics, The International Biometric Society, vol. 77(1), pages 175-185, March.

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