Which measure is estimated in cross-sectional data when Poisson regression with robust standard errors is used?

Study for the ACVPM Epidemiology and Biostatistics Exam. Prepare with flashcards and multiple choice questions, with hints and explanations for each. Be exam-ready!

Multiple Choice

Which measure is estimated in cross-sectional data when Poisson regression with robust standard errors is used?

Explanation:
In cross-sectional data with a binary outcome, Poisson regression with robust standard errors estimates the prevalence ratio. Here, the outcome is measured at a single time point, so the relevant measure of association is how the probability (prevalence) of the outcome differs between exposure groups. The model uses a log link, and the exponentiated coefficients correspond to the ratio of prevalences for a unit change in the predictor. The robust standard errors adjust for the fact that a Poisson variance assumption isn’t correct for a binary outcome, making the inference valid. So the result you get is a prevalence ratio, reflecting how much more (or less) prevalent the outcome is in one group compared with another.

In cross-sectional data with a binary outcome, Poisson regression with robust standard errors estimates the prevalence ratio. Here, the outcome is measured at a single time point, so the relevant measure of association is how the probability (prevalence) of the outcome differs between exposure groups. The model uses a log link, and the exponentiated coefficients correspond to the ratio of prevalences for a unit change in the predictor. The robust standard errors adjust for the fact that a Poisson variance assumption isn’t correct for a binary outcome, making the inference valid. So the result you get is a prevalence ratio, reflecting how much more (or less) prevalent the outcome is in one group compared with another.

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