Abstract
Cohort study is one of the important research methods in analytical epidemiology because of its clear time sequence relationship, which is better than other observational studies in demonstrating causal association. However, screening diagnosis or other methods are often used to exclude the individuals with outcome events during the enrollment process of the subjects in cohort studies. The accuracy of screening diagnosis and the effectiveness of exclusion will affect the accuracy of the baseline status assessment of the subjects included in the study, which may lead to the causal time sequence reversal of exposure-outcome in the estimation of causal effect. Landmark analysis can be used to control reverse causality by excluding subjects with potentially unknown expose-outcome timing. In this paper, we describe the basic principles and analytical steps of landmark analysis, and use data from the Chinese Longitudinal Healthy Longevity Survey to explore the relationship between physical activity and frailty, and introduce the specific application of landmark analysis for the purpose of facilitating its application and inferring causal effects more accurately in cohort studies.
| Translated title of the contribution | Application and case study of landmark analysis in cohort study |
|---|---|
| Original language | Chinese (Traditional) |
| Pages (from-to) | 1808-1814 |
| Number of pages | 7 |
| Journal | Chinese Journal of Epidemiology |
| Volume | 44 |
| Issue number | 11 |
| DOIs | |
| State | Published - 2023 |
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