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1. Linear model theory
: univariate, multivariate, and mixed models
by Muller, Keith E and Stewart, Paul Wilder
2006, 1. Aufl., Wiley series in probability and statistics, ISBN 9780471214885, xiv, 410
A precise and accessible presentation of linear model theory, illustrated with data examplesStatisticians often use linear models for data analysis and for... 
Linear models (Statistics) | Probability & Statistics | General | Mathematics
Book
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2. Generalized linear mixed models
: modern concepts, methods and applications
by Stroup, Walter W
2013, Chapman & Hall/CRC texts in statistical science series., ISBN 1439815127, xxv, 529 pages
"Generalized Linear Mixed Models: Modern Concepts, Methods and Applications presents an introduction to linear modeling using the generalized linear mixed... 
Linear models (Statistics)
Book
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3. Full Text Generalized, linear, and mixed models
by McCulloch, Charles E and Searle, S. R. 1928- (Shayle R.)
2001, 1. Aufl., Wiley series in probability and statistics. Applied probability and statistics section, ISBN 9780471193647, 358
Wiley Series in Probability and Statistics A modern perspective on mixed models The availability of powerful computing methods in recent decades has thrust... 
Linear models (Statistics)
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4. Full Text Linear quantile mixed models
by Geraci, Marco and Bottai, Matteo
Statistics and Computing, ISSN 0960-3174, 5/2014, Volume 24, Issue 3, pp. 461 - 479
Dependent data arise in many studies. Frequently adopted sampling designs, such as cluster, multilevel, spatial, and repeated measures, may induce this... 
Statistics and Computing/Statistics Programs | Best linear predictor | Artificial Intelligence (incl. Robotics) | Statistical Theory and Methods | Statistics | Hierarchical models | Gaussian quadrature | Clarke’s derivative | Probability and Statistics in Computer Science | Clarke's derivative | APPROXIMATION | SUCCIMER | STATISTICS & PROBABILITY | LONGITUDINAL DATA | INFERENCE | DISTRIBUTIONS | REGRESSION QUANTILES | BOOTSTRAP | PANEL-DATA | SMOOTHING SPLINES | ASYMMETRIC LAPLACE DISTRIBUTION | COMPUTER SCIENCE, THEORY & METHODS | Models | Algorithms | Mathematical optimization | Analysis | Quantiles | Maximization | Computer simulation | Computation | Regression | Mathematical models | Optimization
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5. Linear mixed models
: a practical guide using statistical software
by West, Brady T and Welch, Kathleen B and Gałecki, Andrzej T and Gillespie, Brenda W
2015, Second edition., ISBN 1466560991, 414
Linear models (Statistics) | Data processing
Book
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6. Generalized, linear, and mixed models
by McCulloch, Charles E and Searle, S. R. 1928- (Shayle R.) and Neuhaus, John M
2008, 2nd ed., Wiley series in probability and statistics, ISBN 0470073713, xxv, 384
Linear models (Statistics)
Book
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7. Full Text Linear mixed models
: a practical guide using statistical software
by West, Brady T and Galecki, Andrzej T and Welch, Kathleen B and Gillespie, Brenda W
2007, ISBN 1584884800, 1 online resource.
Modèles linéaires (Statistique) | Linear models (Statistics) | Data processing | Informatique
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8. Linear mixed models for longitudinal data
by Verbeke, Geert and Molenberghs, Geert
2009, Springer series in statistics., ISBN 1441902996, xxii, 568
Linear models (Statistics) | Longitudinal method
Book
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9. Repeated measures design with generalized linear mixed models for randomized controlled trials
by Tango, Toshirō, 1950- author
2017, Chapman & Hall/CRC biostatistics series, ISBN 9781498747899, xv, 359 pages
Repeated Measures Design with Generalized Linear Mixed Models for Randomized Controlled Trials is the first book focused on the application of generalized... 
Clinical trials | Linear Models | Statistical methods | methods | Biometry | Randomized Controlled Trials as Topic
Book
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10. Full Text Balancing Type I error and power in linear mixed models
by Matuschek, Hannes and Kliegl, Reinhold and Vasishth, Shravan and Baayen, Harald and Bates, Douglas
Journal of Memory and Language, ISSN 0749-596X, 06/2017, Volume 94, pp. 305 - 315
Linear mixed-effects models have increasingly replaced mixed-model analyses of variance for statistical inference in factorial psycholinguistic experiments.... 
Hypothesis testing | Linear mixed effect model | Power | LINGUISTICS | PSYCHOLOGY, EXPERIMENTAL | PSYCHOLOGY | language | psycholinguistics | language processing | statistical approach | Analysis | Models | Information management | Statistics - Applications
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11. Full Text Polygenic Modeling with Bayesian Sparse Linear Mixed Models
by Zhou, Xiang and Carbonetto, Peter and Stephens, Matthew
PLoS Genetics, ISSN 1553-7390, 02/2013, Volume 9, Issue 2, pp. e1003264 - e1003264
Both linear mixed models (LMMs) and sparse regression models are widely used in genetics applications, including, recently, polygenic modeling in genome-wide... 
QUANTITATIVE TRAIT LOCI | RIDGE-REGRESSION | COMMON SNPS | GENETICS & HEREDITY | POPULATION-STRUCTURE | GENETIC-ASSOCIATION | VARIABLE SELECTION | COMPLEX TRAITS | DAIRY-CATTLE | HERITABILITY | GENOME-WIDE ASSOCIATION | Multifactorial Inheritance - genetics | Genome-Wide Association Study | Markov Chains | Algorithms | Computer Simulation | Humans | Bayes Theorem | Genotype | Models, Genetic | Software | Monte Carlo Method | Bayesian statistical decision theory | Linear models (Statistics) | Research | Linear regression models | Genomics | Studies | Genotype & phenotype | Genetics | Models | Standard deviation | Genomes | Gene expression | Methods | Index Medicus
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12. Full Text Classified Mixed Model Prediction
by Jiang, Jiming and Rao, J. Sunil and Fan, Jie and Nguyen, Thuan
Journal of the American Statistical Association, ISSN 0162-1459, 01/2018, Volume 113, Issue 521, pp. 269 - 279
Many practical problems are related to prediction, where the main interest is at subject (e.g., personalized medicine) or (small) sub-population (e.g., small... 
Mean squared prediction error | Linear mixed model | Mixed effects | CMMP | Future observation | Prediction interval | TRAJECTORIES | SMALL-AREA ESTIMATION | STATISTICS & PROBABILITY | ERROR | CONDITIONAL INFERENCE | Training
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13. Full Text MCMC methods for multi-response generalized linear mixed models: The MCMCglmm R package
by Hadfield, Jarrod D
Journal of Statistical Software, ISSN 1548-7660, 2010, Volume 33, Issue 2, pp. 1 - 22
Generalized linear mixed models provide a flexible framework for modeling a range of data, although with non-Gaussian response variables the likelihood cannot... 
Animal model | Linear mixed model | R | Pedigree | MCMC | Sparse | Phylogeny | Multivariate | DATA AUGMENTATION | HIERARCHICAL-MODELS | ALGORITHM | multivariate | STATISTICS & PROBABILITY | pedigree | PARAMETER EXPANSION | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | MULTILEVEL MODELS | sparse | phylogeny | linear mixed model | animal model
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14. Linear mixed models in practice
: an SAS-oriented approach
by Verbeke, Geert and Molenberghs, Geert and SpringerLink (Online service)
1997, Lecture notes in statistics, ISBN 0387982221, Volume 126, xiii, 306
The dissemination of the MIXED procedure in SAS has provided a whole class of statistical models for routine use. We believe that both the ideas be­ hind the... 
Linear models (Statistics) | Data processing | SAS (Computer file) | Statistics for Life Sciences, Medicine, Health Sciences | Statistics
Book
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15. SAS system for mixed models
by Littell, Ramon C and SAS Institute
1996, ISBN 1555447791, xiv, 633
SAS (Computer file) | Methodology | Mathematical statistics | Statistics
Book
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16. Full Text The anova to mixed model transition
by Boisgontier, Matthieu P and Cheval, Boris
Neuroscience and Biobehavioral Reviews, ISSN 0149-7634, 09/2016, Volume 68, pp. 1004 - 1005
A transition towards mixed models is underway in science. This transition started up because the requirements for using analyses of variances are often not met... 
Neuroscience | Linear mixed-effects models | Statistics | Analysis of variance | BEHAVIORAL SCIENCES | NEUROSCIENCES | Analysis of Variance | Models, Statistical | Analysis | Information management | Neurosciences | Index Medicus
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17. Full Text Improved linear mixed models for genome-wide association studies
by Listgarten, Jennifer and Lippert, Christoph and Kadie, Carl M and Davidson, Robert I and Eskin, Eleazar and Heckerman, David
Nature Methods, ISSN 1548-7091, 06/2012, Volume 9, Issue 6, pp. 525 - 526
BIOCHEMICAL RESEARCH METHODS | Crohn Disease - genetics | Phenotype | Algorithms | Confounding Factors (Epidemiology) | Humans | False Negative Reactions | Linear Models | Polymorphism, Single Nucleotide | False Positive Reactions | Genome-Wide Association Study - methods | Research | Single nucleotide polymorphisms | Index Medicus
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