This course teaches you how to use the NLMIXED procedure to fit statistical models.
Learn How To
use the NLMIXED procedure to fit nonlinear models with random effects and zero-inflated Poisson models deal with the numerical challenges of using the NLMIXED procedure.Who Should Attend
Statisticians, statistically experienced epidemiologists, social scientists, physical scientists, and business analysts
Prerequisites
Before attending this course, you should;
understand categorical data analysis (for example, logistic regression). You can complete the Categorical Data Analysis Using Logistic Regression course or have equivalent experience with and knowledge of logistic regression. understand linear mixed models (the MIXED procedure). You can complete the Mixed Models Analyses Using the SAS System course or have equivalent experience with and knowledge of linear mixed models. have experience with SAS programming at the level covered in the SAS(R) Programming I: Essentials course.SAS Products Covered
SAS/STAT
Course Outline
Overview of Nonlinear Mixed Models and PROC NLMIXED
introduction to nonlinear mixed models Using the NLMIXED procedure for a NLMMApplications of the NLMIXED Procedurefitting zero-inflated Poisson models fitting other mixture models including hurdle models, zero-inlfated negative binomial models, and generalized Poisson models (Self-Study)Computational Efficiencymaking the NLMIXED procedure run faster using techniques achieving convergence with the NLMIXED procedure interpreting log notes and warnings
