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Applied mixed models in medicine / / Helen Brown, Robin Prescott
Applied mixed models in medicine / / Helen Brown, Robin Prescott
Autore Brown Helen <1962->
Edizione [Third edition.]
Pubbl/distr/stampa Chichester, England : , : Wiley, , 2015
Descrizione fisica 1 online resource (539 p.)
Disciplina 610.72/7
Collana Statistics in Practice
Soggetto topico Medicine
ISBN 1-118-77824-3
1-322-52060-7
1-118-77823-5
1-118-77821-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Title Page; Copyright; Contents; Preface to third edition; Mixed models notation; About the Companion Website; Chapter 1 Introduction; 1.1 The use of mixed models; 1.2 Introductory example; 1.2.1 Simple model to assess the effects of treatment (Model A); 1.2.2 A model taking patient effects into account (Model B); 1.2.3 Random effects model (Model C); 1.2.4 Estimation (or prediction) of random effects; 1.3 A multi-centre hypertension trial; 1.3.1 Modelling the data; 1.3.2 Including a baseline covariate (Model B); 1.3.3 Modelling centre effects (Model C)
1.3.4 Including centre-by-treatment interaction effects (Model D)1.3.5 Modelling centre and centre·treatment effects as random (Model E); 1.4 Repeated measures data; 1.4.1 Covariance pattern models; 1.4.2 Random coefficients models; 1.5 More about mixed models; 1.5.1 What is a mixed model?; 1.5.2 Why use mixed models?; 1.5.3 Communicating results; 1.5.4 Mixed models in medicine; 1.5.5 Mixed models in perspective; 1.6 Some useful definitions; 1.6.1 Containment; 1.6.2 Balance; 1.6.3 Error strata; Chapter 2 Normal mixed models; 2.1 Model definition; 2.1.1 The fixed effects model
2.1.2 The mixed model2.1.3 The random effects model covariance structure; 2.1.4 The random coefficients model covariance structure; 2.1.5 The covariance pattern model covariance structure; 2.2 Model fitting methods; 2.2.1 The likelihood function and approaches to its maximisation; 2.2.2 Estimation of fixed effects; 2.2.3 Estimation (or prediction) of random effects and coefficients; 2.2.4 Estimation of variance parameters; 2.3 The Bayesian approach; 2.3.1 Introduction; 2.3.2 Determining the posterior density; 2.3.3 Parameter estimation, probability intervals and p-values
2.3.4 Specifying non-informative prior distributions2.3.5 Evaluating the posterior distribution; 2.4 Practical application and interpretation; 2.4.1 Negative variance components; 2.4.2 Accuracy of variance parameters; 2.4.3 Bias in fixed and random effects standard errors; 2.4.4 Significance testing; 2.4.5 Confidence intervals; 2.4.6 Checking model assumptions; 2.4.7 Missing data; 2.4.8 Determining whether the simulated posterior distribution has converged; 2.5 Example; 2.5.1 Analysis models; 2.5.2 Results; 2.5.3 Discussion of points from Section 2.4; Chapter 3 Generalised linear mixed models
3.1 Generalised linear models3.1.1 Introduction; 3.1.2 Distributions; 3.1.3 The general form for exponential distributions; 3.1.4 The GLM definition; 3.1.5 Fitting the GLM; 3.1.6 Expressing individual distributions in the general exponential form; 3.1.7 Conditional logistic regression; 3.2 Generalised linear mixed models; 3.2.1 The GLMM definition; 3.2.2 The likelihood and quasi-likelihood functions; 3.2.3 Fitting the GLMM; 3.3 Practical application and interpretation; 3.3.1 Specifying binary data; 3.3.2 Uniform effects categories; 3.3.3 Negative variance components
3.3.4 Presentation of fixed and random effects estimates
Record Nr. UNINA-9910132307003321
Brown Helen <1962->  
Chichester, England : , : Wiley, , 2015
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Applied mixed models in medicine / / Helen Brown, Robin Prescott
Applied mixed models in medicine / / Helen Brown, Robin Prescott
Autore Brown Helen <1962->
Edizione [Third edition.]
Pubbl/distr/stampa Chichester, England : , : Wiley, , 2015
Descrizione fisica 1 online resource (539 p.)
Disciplina 610.72/7
Collana Statistics in Practice
Soggetto topico Medicine
ISBN 1-118-77824-3
1-322-52060-7
1-118-77823-5
1-118-77821-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cover; Title Page; Copyright; Contents; Preface to third edition; Mixed models notation; About the Companion Website; Chapter 1 Introduction; 1.1 The use of mixed models; 1.2 Introductory example; 1.2.1 Simple model to assess the effects of treatment (Model A); 1.2.2 A model taking patient effects into account (Model B); 1.2.3 Random effects model (Model C); 1.2.4 Estimation (or prediction) of random effects; 1.3 A multi-centre hypertension trial; 1.3.1 Modelling the data; 1.3.2 Including a baseline covariate (Model B); 1.3.3 Modelling centre effects (Model C)
1.3.4 Including centre-by-treatment interaction effects (Model D)1.3.5 Modelling centre and centre·treatment effects as random (Model E); 1.4 Repeated measures data; 1.4.1 Covariance pattern models; 1.4.2 Random coefficients models; 1.5 More about mixed models; 1.5.1 What is a mixed model?; 1.5.2 Why use mixed models?; 1.5.3 Communicating results; 1.5.4 Mixed models in medicine; 1.5.5 Mixed models in perspective; 1.6 Some useful definitions; 1.6.1 Containment; 1.6.2 Balance; 1.6.3 Error strata; Chapter 2 Normal mixed models; 2.1 Model definition; 2.1.1 The fixed effects model
2.1.2 The mixed model2.1.3 The random effects model covariance structure; 2.1.4 The random coefficients model covariance structure; 2.1.5 The covariance pattern model covariance structure; 2.2 Model fitting methods; 2.2.1 The likelihood function and approaches to its maximisation; 2.2.2 Estimation of fixed effects; 2.2.3 Estimation (or prediction) of random effects and coefficients; 2.2.4 Estimation of variance parameters; 2.3 The Bayesian approach; 2.3.1 Introduction; 2.3.2 Determining the posterior density; 2.3.3 Parameter estimation, probability intervals and p-values
2.3.4 Specifying non-informative prior distributions2.3.5 Evaluating the posterior distribution; 2.4 Practical application and interpretation; 2.4.1 Negative variance components; 2.4.2 Accuracy of variance parameters; 2.4.3 Bias in fixed and random effects standard errors; 2.4.4 Significance testing; 2.4.5 Confidence intervals; 2.4.6 Checking model assumptions; 2.4.7 Missing data; 2.4.8 Determining whether the simulated posterior distribution has converged; 2.5 Example; 2.5.1 Analysis models; 2.5.2 Results; 2.5.3 Discussion of points from Section 2.4; Chapter 3 Generalised linear mixed models
3.1 Generalised linear models3.1.1 Introduction; 3.1.2 Distributions; 3.1.3 The general form for exponential distributions; 3.1.4 The GLM definition; 3.1.5 Fitting the GLM; 3.1.6 Expressing individual distributions in the general exponential form; 3.1.7 Conditional logistic regression; 3.2 Generalised linear mixed models; 3.2.1 The GLMM definition; 3.2.2 The likelihood and quasi-likelihood functions; 3.2.3 Fitting the GLMM; 3.3 Practical application and interpretation; 3.3.1 Specifying binary data; 3.3.2 Uniform effects categories; 3.3.3 Negative variance components
3.3.4 Presentation of fixed and random effects estimates
Record Nr. UNINA-9910810323603321
Brown Helen <1962->  
Chichester, England : , : Wiley, , 2015
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui