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

Formats available	Standard duration
e-Learning:	2.9 hours/180 day license	System Requirements

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 SAS course or have equivalent experience with and knowledge of linear mixed models.
• have experience with SAS programming at the level covered in the SAS Programming 1: Essentials course.

Overview of Nonlinear Mixed Models and PROC NLMIXED

• introduction to nonlinear mixed models
• Using the NLMIXED procedure for a NLMM

Applications of the NLMIXED Procedure

• fitting zero-inflated Poisson models
• fitting other mixture models including hurdle models, zero-inlfated negative binomial models, and generalized Poisson models (Self-Study)

Computational Efficiency

• making the NLMIXED procedure run faster using techniques
• achieving convergence with the NLMIXED procedure
• interpreting log notes and warnings