Abstract
SAS procedure NLIN for fitting nonlinear models is illustrated with applications to growth curves and data from pharmacokinetic and toxicology studies. Generalized linear models, a special type of non-linear models, are introduced and illustrated with applications to logistic and Poisson regression models using LOGISTIC and GENMOD procedures. A separate section covers methods to handle overdispersion, including negative binomial models. The final section applies the GENMOD procedure to Poisson regression with rates. It also explores options provided by the LOGISTIC procedure for applying logistic regression to data with multi-category responses.
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Marasinghe, M.G., Koehler, K.J. (2018). Beyond Regression and Analysis of Variance. In: Statistical Data Analysis Using SAS. Springer Texts in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-69239-5_7
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