Journal ArticleDOI
Approximate inference in generalized linear mixed models
Norman E. Breslow,D. G. Clayton +1 more
TLDR
In this paper, generalized linear mixed models (GLMM) are used to estimate the marginal quasi-likelihood for the mean parameters and the conditional variance for the variances, and the dispersion matrix is specified in terms of a rank deficient inverse covariance matrix.Abstract:
Statistical approaches to overdispersion, correlated errors, shrinkage estimation, and smoothing of regression relationships may be encompassed within the framework of the generalized linear mixed model (GLMM). Given an unobserved vector of random effects, observations are assumed to be conditionally independent with means that depend on the linear predictor through a specified link function and conditional variances that are specified by a variance function, known prior weights and a scale factor. The random effects are assumed to be normally distributed with mean zero and dispersion matrix depending on unknown variance components. For problems involving time series, spatial aggregation and smoothing, the dispersion may be specified in terms of a rank deficient inverse covariance matrix. Approximation of the marginal quasi-likelihood using Laplace's method leads eventually to estimating equations based on penalized quasilikelihood or PQL for the mean parameters and pseudo-likelihood for the variances. Im...read more
Citations
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Journal ArticleDOI
Bias Correction in Generalized Linear Mixed Models with Multiple Components of Dispersion
Xihong Lin,Norman E. Breslow +1 more
TL;DR: In this article, the authors derived general formulas for the asymptotic bias in regression coefficients and variance components estimated by penalized quasi-likelihood (PQL) in generalized linear mixed models with canonical link function and multiple sets of independent random effects.
Journal ArticleDOI
Effects of prolonged and exclusive breastfeeding on child height, weight, adiposity, and blood pressure at age 6.5 y: evidence from a large randomized trial.
Michael S. Kramer,Lidia Matush,Irina Vanilovich,Robert W. Platt,Natalia Bogdanovich,Zinaida Sevkovskaya,Irina Dzikovich,Gyorgy Shishko,Jean-Paul Collet,Richard M. Martin,George Davey Smith,Matthew W. Gillman,Beverley Chalmers,Ellen Hodnett,Stanley H. Shapiro +14 more
TL;DR: The breastfeeding promotion intervention resulted in substantial increases in the duration and exclusivity of breastfeeding, yet it did not reduce the measures of adiposity, increase stature, or reduce blood pressure at age 6.5 y in the experimental group.
Journal ArticleDOI
Statistics in epidemiology: the case-control study
TL;DR: This article presents a general review of the major trends in the conceptualization, development, and success of case-control methods for the study of disease causation and prevention.
Journal ArticleDOI
Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders
Raymond K. Walters,Raymond K. Walters,Renato Polimanti,Emma C. Johnson,Jeanette N. McClintick,Mark Adams,Amy E. Adkins,Fazil Aliev,Silviu-Alin Bacanu,Anthony Batzler,Sarah Bertelsen,Joanna M. Biernacka,Tim B. Bigdeli,Li-Shiun Chen,Toni-Kim Clarke,Yi-Ling Chou,Franziska Degenhardt,Anna R. Docherty,Alexis C. Edwards,Pierre Fontanillas,Jerome C. Foo,Louis Fox,Josef Frank,Ina Giegling,Scott Gordon,Laura M. Hack,Annette M. Hartmann,Sarah M. Hartz,Stefanie Heilmann-Heimbach,Stefan Herms,Stefan Herms,Colin A. Hodgkinson,Per Hoffmann,Per Hoffmann,Jouke-Jan Hottenga,Martin A. Kennedy,Mervi Alanne-Kinnunen,Bettina Konte,Jari Lahti,Marius Lahti-Pulkkinen,Dongbing Lai,Lannie Ligthart,Anu Loukola,Brion S. Maher,Hamdi Mbarek,Andrew M. McIntosh,Matthew B. McQueen,Jacquelyn L. Meyers,Yuri Milaneschi,Teemu Palviainen,John F. Pearson,Roseann E. Peterson,Samuli Ripatti,Euijung Ryu,Nancy L. Saccone,Jessica E. Salvatore,Sandra Sanchez-Roige,Melanie L. Schwandt,Richard Sherva,Fabian Streit,Jana Strohmaier,Nathaniel Thomas,Jen-Chyong Wang,Bradley T. Webb,Robbee Wedow,Leah Wetherill,Amanda G. Wills,Jason D. Boardman,Danfeng Chen,Doo Sup Choi,William E. Copeland,Robert Culverhouse,Norbert Dahmen,Louisa Degenhardt,Benjamin W. Domingue,Sarah L. Elson,Mark A. Frye,Wolfgang Gäbel,Caroline Hayward,Marcus Ising,Margaret Keyes,Falk Kiefer,John Kramer,Samuel Kuperman,Susanne Lucae,Michael T. Lynskey,Wolfgang Maier,Karl Mann,Satu Männistö,Bertram Müller-Myhsok,Alison D. Murray,John I. Nurnberger,Aarno Palotie,Ulrich W. Preuss,Katri Räikkönen,Maureen Reynolds,Monika Ridinger,Norbert Scherbaum,Marc A. Schuckit,Michael Soyka,Michael Soyka,Jens Treutlein,Stephanie H. Witt,Norbert Wodarz,Peter Zill,Daniel E. Adkins,Joseph M. Boden,Dorret I. Boomsma,Laura J. Bierut,Sandra A. Brown,Kathleen K. Bucholz,Sven Cichon,E. Jane Costello,Harriet de Wit,Nancy Diazgranados,Danielle M. Dick,Johan G. Eriksson,Lindsay A. Farrer,Tatiana Foroud,Nathan A. Gillespie,Alison Goate,David Goldman,Richard A. Grucza,Dana B. Hancock,Kathleen Mullan Harris,Andrew C. Heath,Victor Hesselbrock,John K. Hewitt,Christian J. Hopfer,John Horwood,William G. Iacono,Eric O. Johnson,Jaakko Kaprio,Victor M. Karpyak,Kenneth S. Kendler,Henry R. Kranzler,Kenneth Krauter,Paul Lichtenstein,Penelope A. Lind,Matt McGue,James MacKillop,Pamela A. F. Madden,Hermine H. Maes,Patrik K. E. Magnusson,Nicholas G. Martin,Sarah E. Medland,Grant W. Montgomery,Elliot C. Nelson,Markus M. Nöthen,Abraham A. Palmer,Nancy L. Pedersen,Brenda W. J. H. Penninx,Bernice Porjesz,John P. Rice,Marcella Rietschel,Brien P. Riley,Richard J. Rose,Dan Rujescu,Pei-Hong Shen,Judy L. Silberg,Michael C. Stallings,Ralph E. Tarter,Michael M. Vanyukov,Scott I. Vrieze,Tamara L. Wall,John Whitfield,Hongyu Zhao,Benjamin M. Neale,Benjamin M. Neale,Joel Gelernter,Howard J. Edenberg,Arpana Agrawal +171 more
TL;DR: The largest genome-wide association study to date of DSM-IV-diagnosed AD found loci associated with AD and characterized the relationship between AD and other psychiatric and behavioral outcomes, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.
Journal ArticleDOI
On the unnecessary ubiquity of hierarchical linear modeling.
TL;DR: This article compares and contrasts HLM with alternative methods including generalized estimating equations and cluster-robust standard errors and demonstrates the advantages of the alternative methods and also when HLM would be the preferred method.
References
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Journal ArticleDOI
Maximum likelihood from incomplete data via the EM algorithm
Book
Generalized Linear Models
Peter McCullagh,John A. Nelder +1 more
TL;DR: In this paper, a generalization of the analysis of variance is given for these models using log- likelihoods, illustrated by examples relating to four distributions; the Normal, Binomial (probit analysis, etc.), Poisson (contingency tables), and gamma (variance components).
Journal ArticleDOI
Longitudinal data analysis using generalized linear models
Kung Yee Liang,Scott L. Zeger +1 more
TL;DR: In this article, an extension of generalized linear models to the analysis of longitudinal data is proposed, which gives consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence.