Keywords
Generalized linear mixed modelInferenceMathematicsGeneralized linear modelApplied mathematicsMixed modelEconometricsStatisticsComputer scienceArtificial intelligence
Related Publications
Regression Shrinkage and Selection Via the Lasso
SUMMARY We propose a new method for estimation in linear models. The ‘lasso’ minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients b...
Goodness-of-fit measures of <i>R</i> <sup>2</sup> for repeated measures mixed effect models
Linear mixed effects model (LMEM) is efficient in modeling repeated measures longitudinal data. However, little research has been done in developing goodness-of-fit measures tha...
MCMC Methods for Multi-Response Generalized Linear Mixed Models: The<b>MCMCglmm</b><i>R</i>Package
Generalized linear mixed models provide a flexible framework for modeling a range of data, although with non-Gaussian response variables the likelihood cannot be obtained in clo...
Regularization Paths for Generalized Linear Models via Coordinate Descent
We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic regression, and multi- nom...
Inference from Iterative Simulation Using Multiple Sequences
The Gibbs sampler, the algorithm of Metropolis and similar iterative simulation methods are potentially very helpful for summarizing multivariate distributions. Used naively, ho...
Publication Info
- Year
- 1993
- Type
- article
- Volume
- 88
- Issue
- 421
- Pages
- 9-9
- Citations
- 1792
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
1792
OpenAlex
Cite This
N. E. Breslow,
David Clayton
(1993).
Approximate Inference in Generalized Linear Mixed Models.
Journal of the American Statistical Association
, 88
(421)
, 9-9.
https://doi.org/10.2307/2290687
Identifiers
- DOI
- 10.2307/2290687