Isbn: 9781032451909 - bayesian meta-analysis: a practical introduction (16 risultati)

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New. Robert Grant is a statistician who has worked throughout his career with evidence synthesis and Bayesian models. He is one of the developers of Stan software, and a chartered fellow of the Royal Statistical Society. He worked on health service qua.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.

Condizione: New. In English.

Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.

Hardback. Condizione: New. Meta-analysis is the statistical combination of previously conducted studies, often from summary statistics but sometimes with individual participant data. It is widespread in life sciences and is gaining popularity in economics and beyond. In many real-life meta-analyses, challenges in the source information, such as unreported statistics or biases, can be incorporated using Bayesian methods. Bayesian Meta-Analysis: A Practical Introduction provides an approachable introduction for researchers who are new to Bayes, meta-analysis, or both. There is an emphasis on hands-on learning using a variety of software packages.Key FeaturesIntroductory chapters assume no prior experience or mathematical training, and are aimed at non-statistical researchersExamples of basic meta-analyses in seven different software alternatives: BUGS, JAGS, Stan, bayesmeta, brms, Stata, and JASPPractical advice on extracting information from studies, eliciting expert opinions, managing project decisions, and writing up findingsDiscussion of specific problems, including publication bias, unreported statistics, and a mixture of study designs, with code examplesAccompanying online blog and forum, with all code and data from the book, plus more translations to different softwareThis book aims to bridge the gap between the researcher who wants to carry out tailored meta-analysis and the techniques they need, which have previously been available only in mathematically or computationally demanding publications. …

Hardcover. Condizione: Brand New. 336 pages. 10.00x7.00x10.00 inches. In Stock.

Hardback. Condizione: New. Meta-analysis is the statistical combination of previously conducted studies, often from summary statistics but sometimes with individual participant data. It is widespread in life sciences and is gaining popularity in economics and beyond. In many real-life meta-analyses, challenges in the source information, such as unreported statistics or biases, can be incorporated using Bayesian methods. Bayesian Meta-Analysis: A Practical Introduction provides an approachable introduction for researchers who are new to Bayes, meta-analysis, or both. There is an emphasis on hands-on learning using a variety of software packages.Key FeaturesIntroductory chapters assume no prior experience or mathematical training, and are aimed at non-statistical researchersExamples of basic meta-analyses in seven different software alternatives: BUGS, JAGS, Stan, bayesmeta, brms, Stata, and JASPPractical advice on extracting information from studies, eliciting expert opinions, managing project decisions, and writing up findingsDiscussion of specific problems, including publication bias, unreported statistics, and a mixture of study designs, with code examplesAccompanying online blog and forum, with all code and data from the book, plus more translations to different softwareThis book aims to bridge the gap between the researcher who wants to carry out tailored meta-analysis and the techniques they need, which have previously been available only in mathematically or computationally demanding publications. …

Hardcover. Condizione: new. Hardcover. Meta-analysis is the statistical combination of previously conducted studies, often from summary statistics but sometimes with individual participant data. It is widespread in life sciences and is gaining popularity in economics and beyond. In many real-life meta-analyses, challenges in the source information, such as unreported statistics or biases, can be incorporated using Bayesian methods. Bayesian Meta-Analysis: A Practical Introduction provides an approachable introduction for researchers who are new to Bayes, meta-analysis, or both. There is an emphasis on hands-on learning using a variety of software packages.Key FeaturesIntroductory chapters assume no prior experience or mathematical training, and are aimed at non-statistical researchersExamples of basic meta-analyses in seven different software alternatives: BUGS, JAGS, Stan, bayesmeta, brms, Stata, and JASPPractical advice on extracting information from studies, eliciting expert opinions, managing project decisions, and writing up findingsDiscussion of specific problems, including publication bias, unreported statistics, and a mixture of study designs, with code examplesAccompanying online blog and forum, with all code and data from the book, plus more translations to different softwareThis book aims to bridge the gap between the researcher who wants to carry out tailored meta-analysis and the techniques they need, which have previously been available only in mathematically or computationally demanding publications. Provides an approachable introduction for researchers who are new to Bayes, meta-analysis, or both. There is an emphasis on hands-on learning using a variety of software packages. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Meta-analysis is the statistical combination of previously conducted studies, often from summary statistics but sometimes with individual participant data. It is widespread in life sciences and is gaining popularity in economics and beyond. In many real-life meta-analyses, challenges in the source information, such as unreported statistics or biases, can be incorporated using Bayesian methods. Bayesian Meta-Analysis: A Practical Introduction provides an approachable introduction for researchers who are new to Bayes, meta-analysis, or both. There is an emphasis on hands-on learning using a variety of software packages.Key FeaturesIntroductory chapters assume no prior experience or mathematical training, and are aimed at non-statistical researchersExamples of basic meta-analyses in seven different software alternatives: BUGS, JAGS, Stan, bayesmeta, brms, Stata, and JASPPractical advice on extracting information from studies, eliciting expert opinions, managing project decisions, and writing up findingsDiscussion of specific problems, including publication bias, unreported statistics, and a mixture of study designs, with code examplesAccompanying online blog and forum, with all code and data from the book, plus more translations to different softwareThis book aims to bridge the gap between the researcher who wants to carry out tailored meta-analysis and the techniques they need, which have previously been available only in mathematically or computationally demanding publications. 330 pp. Englisch.…

Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Meta-analysis is the statistical combination of previously conducted studies, often from summary statistics but sometimes with individual participant data. It is widespread in life sciences and is gaining popularity in economics and beyond. In many real-life meta-analyses, challenges in the source information, such as unreported statistics or biases, can be incorporated using Bayesian methods. Bayesian Meta-Analysis: A Practical Introduction provides an approachable introduction for researchers who are new to Bayes, meta-analysis, or both. There is an emphasis on hands-on learning using a variety of software packages.Key FeaturesIntroductory chapters assume no prior experience or mathematical training, and are aimed at non-statistical researchersExamples of basic meta-analyses in seven different software alternatives: BUGS, JAGS, Stan, bayesmeta, brms, Stata, and JASPPractical advice on extracting information from studies, eliciting expert opinions, managing project decisions, and writing up findingsDiscussion of specific problems, including publication bias, unreported statistics, and a mixture of study designs, with code examplesAccompanying online blog and forum, with all code and data from the book, plus more translations to different softwareThis book aims to bridge the gap between the researcher who wants to carry out tailored meta-analysis and the techniques they need, which have previously been available only in mathematically or computationally demanding publications.…