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Adaptive Regression for Modeling Nonlinear RelationshipsAdaptive Poisson Regression Modeling of Multivariate Count Outcomes in SAS

Adaptive Regression for Modeling Nonlinear Relationships: Adaptive Poisson Regression Modeling of... [This chapter describes how to use the genreg macro for adaptive Poisson regression modeling of multivariate count outcomes, possibly converted to rates using offsets, as described in Chap. 14 as well as its generated output. Examples are provided for modeling means and dispersions for post-baseline seizure rates in terms of clinic visit, the baseline seizure rate, and being on the anti-epileptic drug progabide as opposed to a placebo. Examples are presented for transition modeling and GEE-based marginal modeling of seizure rates.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

Adaptive Regression for Modeling Nonlinear RelationshipsAdaptive Poisson Regression Modeling of Multivariate Count Outcomes in SAS

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Publisher
Springer International Publishing
Copyright
© Springer International Publishing Switzerland 2016
ISBN
978-3-319-33944-3
Pages
287 –295
DOI
10.1007/978-3-319-33946-7_15
Publisher site
See Chapter on Publisher Site

Abstract

[This chapter describes how to use the genreg macro for adaptive Poisson regression modeling of multivariate count outcomes, possibly converted to rates using offsets, as described in Chap. 14 as well as its generated output. Examples are provided for modeling means and dispersions for post-baseline seizure rates in terms of clinic visit, the baseline seizure rate, and being on the anti-epileptic drug progabide as opposed to a placebo. Examples are presented for transition modeling and GEE-based marginal modeling of seizure rates.]

Published: Sep 21, 2016

Keywords: Generalize Estimate Equation; Variable Count; Adaptive Model; Marginal Model; Primary Predictor

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