Providing software solutions since 1976
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- SAS/STAT Procedures A-Z
The NLMIXED Procedure
- fits mixed models in which the fixed or random effects enter nonlinearly
- enables you to specify a conditional distribution for your data (given the random effects) having either a standard
form or a general distribution that you code using SAS programming statements. The standard forms
include the following:
- normal
- binary
- binomial
- gamma
- negative binomial
- Poisson
- fits nonlinear mixed models by maximizing an approximation to the likelihood integrated over the random effects. Different integral approximations are available, the principal ones being adaptive Gaussian quadrature and a first-order Taylor series approximation.
- enables you to use the estimated model to construct predictions of arbitrary functions by using empirical Bayes estimates of the random effects
- estimate arbitrary functions of the nonrandom parameters and compute their approximate standard errors using the delta method
- construct predictions of an expression across all of the observations in the input data set
- obtain separate analyses on observations in groups
- accommodates models in which different subjects have identical data
- uses ODS to create a SAS data set corresponding to any table
For further details see the SAS/STAT User's Guide:
The NLMIXED Procedure
( PDF | HTML )
Examples
- One-Compartment Model with Pharmacokinetic Data
- Probit-Normal Model with Binomial Data
- Probit-Normal Model with Ordinal Data
- Poisson-Normal Model with Count Data
- Failure Time and Frailty Model
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