EPID 766: Analysis of Longitudinal Data from ... - NCSU Statistics

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CHAPTER 1 Epid 766, D. Zhang 1.1 Review of 3 study designs 1. Cross-sectional study: • Information on disease status (Y ) and exposure status (X) is obtained from a random sample at one time point. A snap shot of population. • A single observation of each variable of interest is measured from each subject: (Yi, Xi) (i = 1, ..., n). Regression such as logistic regression (if Yi is binary) can be used to assess the association between Y and X: � � P[Yi = 1|Xi] log = β0 + β1Xi 1 − P[Yi = 1|Xi] � � P[Y = 1|X = 1]/(1 − P[Y = 1|X = 1]) β1 = log P[Y = 1|X = 0]/(1 − P[Y = 1|X = 0]) β1 = log odds-ratio between exposure population (X = 1) and non exposure population (X = 0). β1 > 0 =⇒ exposure population has higher probability of getting disease. Graduate Summer Session in Epidemiology Slide 6
CHAPTER 1 Epid 766, D. Zhang • Given data as follows, Y = 1 Y = 0 X = 1 n11 n10 X = 0 n01 n00 then the MLE of β1 is given by �β1 = log � n11n00 n10n01 • Feature: All numbers n00, n01, n10, n11 are random. • No causal inference can be made! � β1 may not be stable (e.g., n11 may be too small). Useful public health information can be obtained, such as the proportion of people in the population with disease, the proportion of people in the population under exposure. • Can account for confounders in the model. Graduate Summer Session in Epidemiology Slide 7 �
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