Choosing the frequency of follow-up in longitudinal studies: Is more necessarily better?. Issue 2 (March 2021)

• Record Type: Journal Article
• Authors: Pullenayegum, Eleanor M; Xi, Yao; Lim, Lily; Levin, Jessie; Feldman, Brian M
• Is Part Of: Research methods in medicine & health sciences. Volume 2:Issue 2(2021)
• Page Start: 61
• Page End: 67
• Publication Date: 2021-03
• Subjects: Sample size -- longitudinal data -- correlation -- power; Medicine -- Research -- Periodicals; Medical sciences -- Research -- Periodicals; 610.7205
• DOI: 10.1177/2632084320975260
• Languages: English
• ISSNs: 2632-0843

Abstract

Background: Follow-up frequency is an important design parameter in longitudinal studies. We quantified the impact of reducing follow-up frequency on the precision of estimated regression parameters, and investigated the impact of incorrectly assuming an exchangeable correlation structure on estimates of the loss of precision resulting from reduced follow-up. Methods: We estimated the loss in precision on deleting every second observation from three longitudinal cohorts: patients with Childhood Systemic Lupus Erythematosus (cSLE), the Canadian Haemophilia Prophylaxis Study (CHPS), and patients with Juvenile Dermatomyositis (JDM). We compared these results with those from a theoretical formula assuming an exchangeable correlation structure. Results: The increase in sample size needed to compensate for halving follow-up frequency was 9%, 6% and 28% for the cSLE, CHPS and JDM cohorts respectively. Under the assumption of an exchangeable correlation, the estimated increases in sample size were 22%, 11% and 10% respectively. Conclusions: Reducing follow-up frequency can result in minimal loss of information, as seen in the CHPS cohort. While using a theoretical formula based on an exchangeable correlation structure is convenient, it can be inaccurate when the true correlation structure is not exchangeable.