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Fitting semiparametric random effects models to large data sets.

Publication ,  Journal Article
Pennell, ML; Dunson, DB
Published in: Biostatistics (Oxford, England)
October 2007

For large data sets, it can be difficult or impossible to fit models with random effects using standard algorithms due to memory limitations or high computational burdens. In addition, it would be advantageous to use the abundant information to relax assumptions, such as normality of random effects. Motivated by data from an epidemiologic study of childhood growth, we propose a 2-stage method for fitting semiparametric random effects models to longitudinal data with many subjects. In the first stage, we use a multivariate clustering method to identify G<

Duke Scholars

Published In

Biostatistics (Oxford, England)

DOI

EISSN

1468-4357

ISSN

1465-4644

Publication Date

October 2007

Volume

8

Issue

4

Start / End Page

821 / 834

Related Subject Headings

  • Weight Gain
  • Tobacco Smoke Pollution
  • Statistics & Probability
  • Monte Carlo Method
  • Models, Statistical
  • Markov Chains
  • Longitudinal Studies
  • Infant, Newborn
  • Infant
  • Humans
 

Citation

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Pennell, M. L., & Dunson, D. B. (2007). Fitting semiparametric random effects models to large data sets. Biostatistics (Oxford, England), 8(4), 821–834. https://doi.org/10.1093/biostatistics/kxm008
Pennell, Michael L., and David B. Dunson. “Fitting semiparametric random effects models to large data sets.Biostatistics (Oxford, England) 8, no. 4 (October 2007): 821–34. https://doi.org/10.1093/biostatistics/kxm008.
Pennell ML, Dunson DB. Fitting semiparametric random effects models to large data sets. Biostatistics (Oxford, England). 2007 Oct;8(4):821–34.
Pennell, Michael L., and David B. Dunson. “Fitting semiparametric random effects models to large data sets.Biostatistics (Oxford, England), vol. 8, no. 4, Oct. 2007, pp. 821–34. Epmc, doi:10.1093/biostatistics/kxm008.
Pennell ML, Dunson DB. Fitting semiparametric random effects models to large data sets. Biostatistics (Oxford, England). 2007 Oct;8(4):821–834.
Journal cover image

Published In

Biostatistics (Oxford, England)

DOI

EISSN

1468-4357

ISSN

1465-4644

Publication Date

October 2007

Volume

8

Issue

4

Start / End Page

821 / 834

Related Subject Headings

  • Weight Gain
  • Tobacco Smoke Pollution
  • Statistics & Probability
  • Monte Carlo Method
  • Models, Statistical
  • Markov Chains
  • Longitudinal Studies
  • Infant, Newborn
  • Infant
  • Humans