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Bayesian approaches to clinical trials and health care evaluation [[electronic resource] /] / David J. Spiegelhalter, Keith R. Abrams, Jonathan P. Myles
| Bayesian approaches to clinical trials and health care evaluation [[electronic resource] /] / David J. Spiegelhalter, Keith R. Abrams, Jonathan P. Myles |
| Autore | Spiegelhalter D. J |
| Pubbl/distr/stampa | Chichester ; ; Hoboken, NJ, : Wiley, c2004 |
| Descrizione fisica | 1 online resource (408 p.) |
| Disciplina |
519.5/42/02461
610.72 |
| Altri autori (Persone) |
AbramsK. R (Keith R.)
MylesJonathan P |
| Collana | Statistics in practice |
| Soggetto topico |
Bayesian statistical decision theory
Medicine - Research - Statistical methods Clinical trials - Statistical methods |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-26930-8
9786610269303 0-470-09259-9 0-470-09260-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Bayesian Approaches to Clinical Trials and Health-Care Evaluation; Contents; Preface; List of examples; 1 Introduction; 1.1 What are Bayesian methods?; 1.2 What do we mean by 'health-care evaluation'?; 1.3 A Bayesian approach to evaluation; 1.4 The aim of this book and the intended audience; 1.5 Structure of the book; 2 Basic Concepts from Traditional Statistical Analysis; 2.1 Probability; 2.1.1 What is probability?; 2.1.2 Odds and log-odds; 2.1.3 Bayes theorem for simple events; 2.2 Random variables, parameters and likelihood; 2.2.1 Random variables and their distributions
2.2.2 Expectation, variance, covariance and correlation 2.2.3 Parametric distributions and conditional independence; 2.2.4 Likelihoods; 2.3 The normal distribution; 2.4 Normal likelihoods; 2.4.1 Normal approximations for binary data; 2.4.2 Normal likelihoods for survival data; 2.4.3 Normal likelihoods for count responses; 2.4.4 Normal likelihoods for continuous responses; 2.5 Classical inference; 2.6 A catalogue of useful distributions*; 2.6.1 Binomial and Bernoulli; 2.6.2 Poisson; 2.6.3 Beta; 2.6.4 Uniform; 2.6.5 Gamma; 2.6.6 Root-inverse-gamma; 2.6.7 Half-normal; 2.6.8 Log-normal 2.6.9 Student's 2.6.10 Bivariate normal; 2.7 Key points; Exercises; 3 An Overview of the Bayesian Approach; 3.1 Subjectivity and context; 3.2 Bayes theorem for two hypotheses; 3.3 Comparing simple hypotheses: likelihood ratios and Bayes factors; 3.4 Exchangeability and parametric modelling*; 3.5 Bayes theorem for general quantities; 3.6 Bayesian analysis with binary data; 3.6.1 Binary data with a discrete prior distribution; 3.6.2 Conjugate analysis for binary data; 3.7 Bayesian analysis with normal distributions; 3.8 Point estimation, interval estimation and interval hypotheses 3.9 The prior distribution 3.10 How to use Bayes theorem to interpret trial results; 3.11 The 'credibility' of significant trial results*; 3.12 Sequential use of Bayes theorem*; 3.13 Predictions; 3.13.1 Predictions in the Bayesian framework; 3.13.2 Predictions for binary data*; 3.13.3 Predictions for normal data; 3.14 Decision-making; 3.15 Design; 3.16 Use of historical data; 3.17 Multiplicity, exchangeability and hierarchical models; 3.18 Dealing with nuisance parameters*; 3.18.1 Alternative methods for eliminating nuisance parameters*; 3.18.2 Profile likelihood in a hierarchical model* 3.19 Computational issues 3.19.1 Monte Carlo methods; 3.19.2 Markov chain Monte Carlo methods; 3.19.3 WinBUGS; 3.20 Schools of Bayesians; 3.21 A Bayesian checklist; 3.22 Further reading; 3.23 Key points; Exercises; 4 Comparison of Alternative Approaches to Inference; 4.1 A structure for alternative approaches; 4.2 Conventional statistical methods used in health-care evaluation; 4.3 The likelihood principle, sequential analysis and types of error; 4.3.1 The likelihood principle; 4.3.2 Sequential analysis; 4.3.3 Type I and Type II error; 4.4 P-values and Bayes factors* 4.4.1 Criticism of P-values |
| Record Nr. | UNINA-9910143509603321 |
Spiegelhalter D. J
|
||
| Chichester ; ; Hoboken, NJ, : Wiley, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Bayesian approaches to clinical trials and health care evaluation [[electronic resource] /] / David J. Spiegelhalter, Keith R. Abrams, Jonathan P. Myles
| Bayesian approaches to clinical trials and health care evaluation [[electronic resource] /] / David J. Spiegelhalter, Keith R. Abrams, Jonathan P. Myles |
| Autore | Spiegelhalter D. J |
| Pubbl/distr/stampa | Chichester ; ; Hoboken, NJ, : Wiley, c2004 |
| Descrizione fisica | 1 online resource (408 p.) |
| Disciplina |
519.5/42/02461
610.72 |
| Altri autori (Persone) |
AbramsK. R (Keith R.)
MylesJonathan P |
| Collana | Statistics in practice |
| Soggetto topico |
Bayesian statistical decision theory
Medicine - Research - Statistical methods Clinical trials - Statistical methods |
| ISBN |
1-280-26930-8
9786610269303 0-470-09259-9 0-470-09260-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Bayesian Approaches to Clinical Trials and Health-Care Evaluation; Contents; Preface; List of examples; 1 Introduction; 1.1 What are Bayesian methods?; 1.2 What do we mean by 'health-care evaluation'?; 1.3 A Bayesian approach to evaluation; 1.4 The aim of this book and the intended audience; 1.5 Structure of the book; 2 Basic Concepts from Traditional Statistical Analysis; 2.1 Probability; 2.1.1 What is probability?; 2.1.2 Odds and log-odds; 2.1.3 Bayes theorem for simple events; 2.2 Random variables, parameters and likelihood; 2.2.1 Random variables and their distributions
2.2.2 Expectation, variance, covariance and correlation 2.2.3 Parametric distributions and conditional independence; 2.2.4 Likelihoods; 2.3 The normal distribution; 2.4 Normal likelihoods; 2.4.1 Normal approximations for binary data; 2.4.2 Normal likelihoods for survival data; 2.4.3 Normal likelihoods for count responses; 2.4.4 Normal likelihoods for continuous responses; 2.5 Classical inference; 2.6 A catalogue of useful distributions*; 2.6.1 Binomial and Bernoulli; 2.6.2 Poisson; 2.6.3 Beta; 2.6.4 Uniform; 2.6.5 Gamma; 2.6.6 Root-inverse-gamma; 2.6.7 Half-normal; 2.6.8 Log-normal 2.6.9 Student's 2.6.10 Bivariate normal; 2.7 Key points; Exercises; 3 An Overview of the Bayesian Approach; 3.1 Subjectivity and context; 3.2 Bayes theorem for two hypotheses; 3.3 Comparing simple hypotheses: likelihood ratios and Bayes factors; 3.4 Exchangeability and parametric modelling*; 3.5 Bayes theorem for general quantities; 3.6 Bayesian analysis with binary data; 3.6.1 Binary data with a discrete prior distribution; 3.6.2 Conjugate analysis for binary data; 3.7 Bayesian analysis with normal distributions; 3.8 Point estimation, interval estimation and interval hypotheses 3.9 The prior distribution 3.10 How to use Bayes theorem to interpret trial results; 3.11 The 'credibility' of significant trial results*; 3.12 Sequential use of Bayes theorem*; 3.13 Predictions; 3.13.1 Predictions in the Bayesian framework; 3.13.2 Predictions for binary data*; 3.13.3 Predictions for normal data; 3.14 Decision-making; 3.15 Design; 3.16 Use of historical data; 3.17 Multiplicity, exchangeability and hierarchical models; 3.18 Dealing with nuisance parameters*; 3.18.1 Alternative methods for eliminating nuisance parameters*; 3.18.2 Profile likelihood in a hierarchical model* 3.19 Computational issues 3.19.1 Monte Carlo methods; 3.19.2 Markov chain Monte Carlo methods; 3.19.3 WinBUGS; 3.20 Schools of Bayesians; 3.21 A Bayesian checklist; 3.22 Further reading; 3.23 Key points; Exercises; 4 Comparison of Alternative Approaches to Inference; 4.1 A structure for alternative approaches; 4.2 Conventional statistical methods used in health-care evaluation; 4.3 The likelihood principle, sequential analysis and types of error; 4.3.1 The likelihood principle; 4.3.2 Sequential analysis; 4.3.3 Type I and Type II error; 4.4 P-values and Bayes factors* 4.4.1 Criticism of P-values |
| Record Nr. | UNINA-9910830922703321 |
|
Spiegelhalter D. J
|
||
| Chichester ; ; Hoboken, NJ, : Wiley, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Bayesian approaches to clinical trials and health care evaluation / / David J. Spiegelhalter, Keith R. Abrams, Jonathan P. Myles
| Bayesian approaches to clinical trials and health care evaluation / / David J. Spiegelhalter, Keith R. Abrams, Jonathan P. Myles |
| Autore | Spiegelhalter D. J |
| Pubbl/distr/stampa | Chichester ; ; Hoboken, NJ, : Wiley, c2004 |
| Descrizione fisica | 1 online resource (408 p.) |
| Disciplina | 519.5/42/02461 |
| Altri autori (Persone) |
AbramsK. R (Keith R.)
MylesJonathan P |
| Collana | Statistics in practice |
| Soggetto topico |
Bayesian statistical decision theory
Medicine - Research - Statistical methods Clinical trials - Statistical methods |
| ISBN |
1-280-26930-8
9786610269303 0-470-09259-9 0-470-09260-2 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Bayesian Approaches to Clinical Trials and Health-Care Evaluation; Contents; Preface; List of examples; 1 Introduction; 1.1 What are Bayesian methods?; 1.2 What do we mean by 'health-care evaluation'?; 1.3 A Bayesian approach to evaluation; 1.4 The aim of this book and the intended audience; 1.5 Structure of the book; 2 Basic Concepts from Traditional Statistical Analysis; 2.1 Probability; 2.1.1 What is probability?; 2.1.2 Odds and log-odds; 2.1.3 Bayes theorem for simple events; 2.2 Random variables, parameters and likelihood; 2.2.1 Random variables and their distributions
2.2.2 Expectation, variance, covariance and correlation 2.2.3 Parametric distributions and conditional independence; 2.2.4 Likelihoods; 2.3 The normal distribution; 2.4 Normal likelihoods; 2.4.1 Normal approximations for binary data; 2.4.2 Normal likelihoods for survival data; 2.4.3 Normal likelihoods for count responses; 2.4.4 Normal likelihoods for continuous responses; 2.5 Classical inference; 2.6 A catalogue of useful distributions*; 2.6.1 Binomial and Bernoulli; 2.6.2 Poisson; 2.6.3 Beta; 2.6.4 Uniform; 2.6.5 Gamma; 2.6.6 Root-inverse-gamma; 2.6.7 Half-normal; 2.6.8 Log-normal 2.6.9 Student's 2.6.10 Bivariate normal; 2.7 Key points; Exercises; 3 An Overview of the Bayesian Approach; 3.1 Subjectivity and context; 3.2 Bayes theorem for two hypotheses; 3.3 Comparing simple hypotheses: likelihood ratios and Bayes factors; 3.4 Exchangeability and parametric modelling*; 3.5 Bayes theorem for general quantities; 3.6 Bayesian analysis with binary data; 3.6.1 Binary data with a discrete prior distribution; 3.6.2 Conjugate analysis for binary data; 3.7 Bayesian analysis with normal distributions; 3.8 Point estimation, interval estimation and interval hypotheses 3.9 The prior distribution 3.10 How to use Bayes theorem to interpret trial results; 3.11 The 'credibility' of significant trial results*; 3.12 Sequential use of Bayes theorem*; 3.13 Predictions; 3.13.1 Predictions in the Bayesian framework; 3.13.2 Predictions for binary data*; 3.13.3 Predictions for normal data; 3.14 Decision-making; 3.15 Design; 3.16 Use of historical data; 3.17 Multiplicity, exchangeability and hierarchical models; 3.18 Dealing with nuisance parameters*; 3.18.1 Alternative methods for eliminating nuisance parameters*; 3.18.2 Profile likelihood in a hierarchical model* 3.19 Computational issues 3.19.1 Monte Carlo methods; 3.19.2 Markov chain Monte Carlo methods; 3.19.3 WinBUGS; 3.20 Schools of Bayesians; 3.21 A Bayesian checklist; 3.22 Further reading; 3.23 Key points; Exercises; 4 Comparison of Alternative Approaches to Inference; 4.1 A structure for alternative approaches; 4.2 Conventional statistical methods used in health-care evaluation; 4.3 The likelihood principle, sequential analysis and types of error; 4.3.1 The likelihood principle; 4.3.2 Sequential analysis; 4.3.3 Type I and Type II error; 4.4 P-values and Bayes factors* 4.4.1 Criticism of P-values |
| Record Nr. | UNINA-9910877647303321 |
|
Spiegelhalter D. J
|
||
| Chichester ; ; Hoboken, NJ, : Wiley, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||