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Tracing studies in cohorts with attrition: Selection models for efficient sampling.

Nathalie C Moon1, Leilei Zeng1, Richard J Cook1

  • 1Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, ON, Canada.

Statistics in Medicine
|April 24, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces selection models to improve tracing studies for chronic disease cohorts. These methods efficiently sample individuals lost to follow-up, enhancing data recovery and analysis for disease progression research.

Keywords:
Markov modelattritioninception cohortselection modelsequentially missing at randomtracing

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Longitudinal Studies

Background:

  • Chronic disease cohort studies track individuals to understand risk factors' impact on disease progression and mortality.
  • Loss to follow-up in cohort studies results in significant information loss, potentially biasing results.
  • Tracing studies can recover some lost information but require efficient sampling strategies.

Purpose of the Study:

  • To develop and evaluate novel selection models for sampling individuals in tracing studies.
  • To enhance the efficiency of estimators compared to simple random sampling in cohort follow-up.
  • To incorporate cost constraints into efficient sampling schemes for tracing studies.

Main Methods:

  • Utilized selection models to identify optimal subsamples of individuals lost to follow-up for tracing.
  • Developed efficient sampling schemes that account for cost constraints.
  • Applied the proposed methods to data from the University of Toronto Psoriatic Arthritis Cohort.

Main Results:

  • Selection models yielded more efficient estimators than simple random sampling for tracing studies.
  • Developed sampling schemes demonstrated good performance under cost constraints.
  • The application illustrated the practical utility of the methods in a real-world cohort.

Conclusions:

  • Selection models offer a statistically sound and efficient approach to mitigate information loss due to withdrawal in chronic disease cohorts.
  • The proposed cost-constrained sampling schemes are effective for optimizing tracing study resources.
  • These methods improve the reliability of findings from longitudinal studies with participant attrition.