ArticleStatistical methods in medical research2017
Sample size calculations for prevalent cohort designs.
Article in Statistical methods in medical research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Retention in care of HIV-exposed infants and associated infant and maternal factors in Teso Sub Region, Eastern Uganda.AIDS research and therapy · 2026Article
- Evaluating and predicting exclusive breastfeeding behaviour based on an energy vitality model during women's lactation: a longitudinal study.BMC pregnancy and childbirth · 2025Article
- Trends in emotional functioning and psychosocial wellbeing in breast cancer survivors: a prospective cohort study using patient-reported outcome measures.BMC women's health · 2023Article
- Factors associated with post NICU discharge exclusive breastfeeding rate and duration amongst first time mothers of preterm infants in Shanghai: a longitudinal cohort study.International breastfeeding journal · 2022Article
- Rationale and design of a prospective, multicenter, cohort study on the evaluation of postoperative Venous ThromboEmbolism incidence in patients with ColoRectal Cancer (CRC-VTE trial).Translational cancer research · 2022Article
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Authors and funding
4 authors.
Funding
Abstract
Cross-sectional prevalent cohort design has drawn considerable interests in the studies of association between risk factors and time-to-event outcome. The sampling scheme in such design gives rise to length-biased data that require specialized analysis strategy but can improve study efficiency. The power and sample size calculation methods are however lacking for studies with prevalent cohort design, and using the formula developed for traditional survival data may overestimate sample size. We derive the sample size formulas that are appropriate for the design of cross-sectional prevalent cohort studies, under the assumptions of exponentially distributed event time and uniform follow-up for cross-sectional prevalent cohort design. We perform numerical and simulation studies to compare the sample size requirements for achieving the same power between prevalent cohort and incident cohort designs. We also use a large prospective prevalent cohort study to demonstrate the procedure. Using rigorous designs and proper analysis tools, the prospective prevalent cohort design can be more efficient than the incident cohort design with the same total sample sizes and study durations.
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