Core Guide: Longitudinal Data Analysis - Duke University

Core Guide: Longitudinal data Analysis 1 | P a g e Core Guide: Longitudinal data Analysis Part of a series addressing common issues in statistical and epidemiological design and Analysis Background In contrast to cross-sectional data , which are collected at a single time point, Longitudinal data are collected at multiple time points on the same individuals over time. These so called repeated measures data may be related to an exposure, or an outcome/event, or both. The primary benefit of collecting Longitudinal data is the ability to prospectively record the health outcome, as well as to measure an exposure that may be associated with this outcome. Longitudinal studies are generally considered superior to cross-sectional studies in validly estimating risk; and prospectively measuring an exposure will reduce the possibility of misclassification of this exposure that frequently occurs in retrospective studies.

Oct 05, 2017 · zero. This paired analysis will give us the exact same result (T-statistic) as the one-sample T-test above. In the event that our outcome is binary (e.g., 0/1), we could perform a paired test of categorical data, such as a McNemar’s test to test the null hypothesis: is the proportion of participants with the event

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  Analysis, Data, Categorical, Data analysis, Categorical data

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