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Bayesian subcohort selection for longitudinal covariate measurements in follow‐up studies

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  • Jaakko Reinikainen
  • Juha Karvanen

Abstract

We propose an approach for the planning of longitudinal covariate measurements in follow‐up studies where covariates are time‐varying. We assume that the entire cohort cannot be selected for longitudinal measurements due to financial limitations, and study how a subset of the cohort should be selected optimally, in order to obtain precise estimates of covariate effects in a survival model. In our approach, the study will be designed sequentially utilizing the data collected in previous measurements of the individuals as prior information. We propose using a Bayesian optimality criterion in the subcohort selections, which is compared with simple random sampling using simulated and real follow‐up data. Our work improves the computational approach compared to the previous research on the topic so that designs with several covariates and measurement points can be implemented. As an example we derive the optimal design for studying the effect of body mass index and smoking on all‐cause mortality in a Finnish longitudinal study. Our results support the conclusion that the precision of the estimates can be clearly improved by optimal design.

Suggested Citation

  • Jaakko Reinikainen & Juha Karvanen, 2022. "Bayesian subcohort selection for longitudinal covariate measurements in follow‐up studies," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 76(4), pages 372-390, November.
    • Handle: RePEc:bla:stanee:v:76:y:2022:i:4:p:372-390
    DOI: 10.1111/stan.12264
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    References listed on IDEAS

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    1. A. C. Atkinson & C. G. B. Demetrio & S. S. Zocchi, 1995. "Optimum Dose Levels When Males and Females Differ in Response," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 44(2), pages 213-226, June.
    2. Manuela Buzoianu & Joseph B. Kadane, 2009. "Optimal Bayesian Design for Patient Selection in a Clinical Study," Biometrics, The International Biometric Society, vol. 65(3), pages 953-961, September.
    3. Juha Mehtälä & Kari Auranen & Sangita Kulathinal, 2015. "Optimal observation times for multistate Markov models—applications to pneumococcal colonization studies," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 64(3), pages 451-468, April.
    4. Stephen E. Wright & A. John Bailer, 2006. "Optimal Experimental Design for a Nonlinear Response in Environmental Toxicology," Biometrics, The International Biometric Society, vol. 62(3), pages 886-892, September.
    5. Wenguang Sun & Marshall M. Joffe & Jinbo Chen & Steven M. Brunelli, 2010. "Design and Analysis of Multiple Events Case–Control Studies," Biometrics, The International Biometric Society, vol. 66(4), pages 1220-1229, December.
    6. Olli Saarela & Sangita Kulathinal & Juha Karvanen, 2012. "Secondary Analysis under Cohort Sampling Designs Using Conditional Likelihood," Journal of Probability and Statistics, Hindawi, vol. 2012, pages 1-37, April.
    7. Karvanen, Juha & Kulathinal, Sangita & Gasbarra, Dario, 2009. "Optimal designs to select individuals for genotyping conditional on observed binary or survival outcomes and non-genetic covariates," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1782-1793, March.
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