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SNP_NLMM: A SAS Macro to Implement a Flexible Random Effects Density for Generalized Linear and Nonlinear Mixed Models.

Publication ,  Journal Article
Vock, DM; Davidian, M; Tsiatis, AA
Published in: J Stat Softw
January 1, 2014

Generalized linear and nonlinear mixed models (GMMMs and NLMMs) are commonly used to represent non-Gaussian or nonlinear longitudinal or clustered data. A common assumption is that the random effects are Gaussian. However, this assumption may be unrealistic in some applications, and misspecification of the random effects density may lead to maximum likelihood parameter estimators that are inconsistent, biased, and inefficient. Because testing if the random effects are Gaussian is difficult, previous research has recommended using a flexible random effects density. However, computational limitations have precluded widespread use of flexible random effects densities for GLMMs and NLMMs. We develop a SAS macro, SNP_NLMM, that overcomes the computational challenges to fit GLMMs and NLMMs where the random effects are assumed to follow a smooth density that can be represented by the seminonparametric formulation proposed by Gallant and Nychka (1987). The macro is flexible enough to allow for any density of the response conditional on the random effects and any nonlinear mean trajectory. We demonstrate the SNP_NLMM macro on a GLMM of the disease progression of toenail infection and on a NLMM of intravenous drug concentration over time.

Duke Scholars

Published In

J Stat Softw

DOI

ISSN

1548-7660

Publication Date

January 1, 2014

Volume

56

Start / End Page

2

Location

United States

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 0104 Statistics
 

Citation

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Vock, D. M., Davidian, M., & Tsiatis, A. A. (2014). SNP_NLMM: A SAS Macro to Implement a Flexible Random Effects Density for Generalized Linear and Nonlinear Mixed Models. J Stat Softw, 56, 2. https://doi.org/10.18637/jss.v056.c02
Vock, David M., Marie Davidian, and Anastasios A. Tsiatis. “SNP_NLMM: A SAS Macro to Implement a Flexible Random Effects Density for Generalized Linear and Nonlinear Mixed Models.J Stat Softw 56 (January 1, 2014): 2. https://doi.org/10.18637/jss.v056.c02.
Vock, David M., et al. “SNP_NLMM: A SAS Macro to Implement a Flexible Random Effects Density for Generalized Linear and Nonlinear Mixed Models.J Stat Softw, vol. 56, Jan. 2014, p. 2. Pubmed, doi:10.18637/jss.v056.c02.

Published In

J Stat Softw

DOI

ISSN

1548-7660

Publication Date

January 1, 2014

Volume

56

Start / End Page

2

Location

United States

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 0104 Statistics