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Resampling Procedures for Making Inference under Nested Case-control Studies.

Tianxi Cai1, Yingye Zheng2

  • 1Department of Biostatistics, Harvarfad University, Boston, MA, USA.

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|January 18, 2014
PubMed
Summary
This summary is machine-generated.

Nested case-control studies use inverse probability weighting (IPW) for risk assessment. A new resampling procedure offers valid interval estimation for IPW estimators, overcoming limitations of standard methods.

Keywords:
Biomarker studyInterval EstimationInverse Probability WeightingNested case-control studyResampling methods, Risk PredictionSimultaneous Confidence BandSurvival Model

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Area of Science:

  • Biostatistics
  • Epidemiology
  • Statistical Genetics

Background:

  • Nested case-control (NCC) designs are cost-effective for large cohort studies using expensive biomarkers.
  • Existing methods for NCC data, like conditional logistic regression, have limitations in model flexibility and assumptions.
  • Inverse probability weighting (IPW) offers a more general approach but faces challenges in interval estimation due to complex correlations.

Purpose of the Study:

  • To develop a valid resampling procedure for interval estimation of inverse probability weighting (IPW) estimators in nested case-control (NCC) studies.
  • To address the challenges in estimating the distribution of IPW estimators, particularly with non-smooth functions and simultaneous inferences.
  • To provide a practical alternative to standard resampling methods like the bootstrap, which are not suitable for NCC data.

Main Methods:

  • Proposed a novel resampling procedure designed to accommodate the specific correlation structure of NCC studies.
  • Developed methods for valid interval estimation of a broad class of IPW estimators.
  • Validated the proposed procedure through simulation studies.

Main Results:

  • The proposed resampling procedure provides valid estimates for the distribution of IPW estimators.
  • Simulation results demonstrate good performance, especially when analytical variance estimation is difficult or suboptimal.
  • The method was successfully applied to the Framingham Offspring Study data.

Conclusions:

  • The new resampling procedure effectively addresses the challenges of interval estimation in NCC studies using IPW.
  • This method offers a robust and applicable tool for risk assessment with complex biomarkers in large cohort studies.
  • The approach enhances the utility of IPW estimators in epidemiological research, exemplified by cardiovascular risk assessment.