A Gaussian linear model for treats the transformed observations as having additive constant-variance errors and models as linear. A Poisson regression with square-root link retains the Poisson likelihood and modelsThe two procedures therefore have different likelihoods, fitted means, and constraints; transforming the response is not the same as transforming its conditional mean.
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