Yet Another Blog in Statistical Computing

I can calculate the motion of heavenly bodies but not the madness of people. -Isaac Newton

Modeling Rates and Proportions in SAS – 1

In practice, OLS (Ordinary Least Square) regression has been widely used to model rates and proportions bounded between 0 and 1 due to its simplicity. However, the conditional distribution of an OLS regression model is assumed Gaussian N(X`B, sigma ^ 2), which is questionable for a variate in the open interval (0, 1). In this paper, we surveyed six alternatives modeling methods for such outcomes, including OLS regression with the LOGIT transformation, NLS (Nonlinear Least Square) regression, Tobit model, Beta model, Simplex model, and Fractional LOGIT model, and demonstrated their implementations in SAS through a data analysis exercise. The purpose of my study is to provide a comprehensive survey in SAS user community on how to model percentage and proportion outcomes in SAS.

Rate and Proportion outcomes, OLS, NLS, Tobit, Beta, Simplex, Fractional LOGIT, PROC NLMIXED


Written by statcompute

February 25, 2012 at 8:49 pm

Posted in Statistical Models

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