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Two-wave two-phase outcome-dependent sampling designs, with applications to longitudinal binary data.

Ran Tao1,2, Nathaniel D Mercaldo3, Sebastien Haneuse4

  • 1Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.

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Summary
This summary is machine-generated.

This study introduces novel two-wave two-phase outcome-dependent sampling (ODS) designs for longitudinal binary data. These adaptive designs optimize resource allocation for efficient estimation of covariate effects in cohort studies.

Keywords:
ascertainment corrected maximum likelihoodmarginal modelmarginalized modelmultiple imputationmultiwave designtime-dependent covariate

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Area of Science:

  • Biostatistics
  • Epidemiology
  • Longitudinal Data Analysis

Background:

  • Resource constraints often limit exposure ascertainment in large studies.
  • Existing outcome-dependent sampling (ODS) designs are effective for time-varying covariates but suboptimal for time-invariant or joint covariate effects.
  • The optimal design for longitudinal binary data with mixed covariate types under ODS is not well-defined.

Purpose of the Study:

  • To propose a new class of two-wave two-phase ODS designs for longitudinal binary data.
  • To address the challenge of efficiently estimating associations involving time-invariant covariates in longitudinal studies.
  • To enhance study success by optimizing sample selection through interim design evaluation.

Main Methods:

  • Introduced a two-wave sampling strategy within the second phase of ODS.
  • Incorporated an interim design evaluation using first-wave data.
  • Utilized simulation-based searches to identify optimal second-wave sampling probabilities for improved estimation efficiency.

Main Results:

  • The proposed two-wave ODS designs offer flexibility in optimizing estimation efficiency when the second-phase sample size is fixed.
  • These designs allow for tailoring sample sizes to achieve desired precision when relative sampling probabilities are fixed.
  • Demonstrated the application and characteristics of the proposed designs using the Lung Health Study as an exemplar.

Conclusions:

  • The novel two-wave two-phase ODS designs provide a robust framework for longitudinal binary data analysis, particularly when assessing time-invariant covariates.
  • These adaptive designs improve the efficiency and likelihood of study success under resource constraints.
  • The methodology is generalizable to various response distributions beyond binary outcomes.