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Bayesian analysis made simple: an Excel GUI for WinBUGS / Woodward, Phillip (2012)
Titre : Bayesian analysis made simple: an Excel GUI for WinBUGS Type de document : livre Auteurs : Woodward, Phillip Editeur : Boca Raton, Florida : CRC Press AnnÃ©e de publication : 2012 Collection : Chapman & Hall/CRC Biostatistics series Importance : 342 p. ISBN/ISSN/EAN : 9781439839546 Langues : Anglais (eng) MotsclÃ©s : Bayesian statistical decision theory Case studies Statistical methods RÃ©sumÃ© : "Although the popularity of the Bayesian approach to statistics has been growing for years, many still think of it as somewhat esoteric, not focused on practical issues, or generally too difficult to understand.Bayesian Analysis Made Simple is aimed at those who wish to apply Bayesian methods but either are not experts or do not have the time to create WinBUGS code and ancillary files for every analysis they undertake. Accessible to even those who would not routinely use Excel, this book provides a custommade Excel GUI, immediately useful to those users who want to be able to quickly apply Bayesian methods without being distracted by computing or mathematical issues.From simple NLMs to complex GLMMs and beyond, Bayesian Analysis Made Simple describes how to use Excel for a vast range of Bayesian models in an intuitive manner accessible to the statistically savvy user. Packed with relevant case studies, this book is for any data analyst wishing to apply Bayesian methods to analyze their data, from professional statisticians to statistically aware scientists" "Preface Although the popularity of the Bayesian approach to statistics has been growing rapidly for many years, among those working in business and industry there are still many who think of it as somewhat esoteric, not focused on practical issues, or generally quite difficult to understand. This view may be partly due to the relatively few books that focus primarily on how to apply Bayesian methods to a wide range of common problems. I believe that the essence of the approach is not only much more relevant to the scientific problems that require statistical thinking and methods, but also much easier to understand and explain to the wider scientific community. But being convinced of the benefits of the Bayesian approach is not enough if the person charged with analyzing the data does not have the computing software tools to implement these methods. Although WinBUGS (Lunn et al. 2000) provides sufficient functionality for the vast majority of data analyses that are undertaken, there is still a steep learning curve associated with the programming language that many will not have the time or motivation to overcome. This book describes a graphical user interface (GUI) for WinBUGS, BugsXLA, the purpose of which is to make Bayesian analysis relatively simple. Since I have always been an advocate of Excel as a tool for exploratory graphical analysis of data (somewhat against the antiExcel feelings in the statistical community generally), I created BugsXLA as an Excel addin. Other than to calculate some simple summary statistics from the data, Excel is only used as a convenient vehicle to store the data, plus some metadata used by BugsXLA, as well as a home for the Visual Basic program itself" Bayesian analysis made simple: an Excel GUI for WinBUGS [livre] / Woodward, Phillip .  Boca Raton, Florida : CRC Press, 2012 .  342 p..  (Chapman & Hall/CRC Biostatistics series) .
ISBN : 9781439839546
Langues : Anglais (eng)
MotsclÃ©s : Bayesian statistical decision theory Case studies Statistical methods RÃ©sumÃ© : "Although the popularity of the Bayesian approach to statistics has been growing for years, many still think of it as somewhat esoteric, not focused on practical issues, or generally too difficult to understand.Bayesian Analysis Made Simple is aimed at those who wish to apply Bayesian methods but either are not experts or do not have the time to create WinBUGS code and ancillary files for every analysis they undertake. Accessible to even those who would not routinely use Excel, this book provides a custommade Excel GUI, immediately useful to those users who want to be able to quickly apply Bayesian methods without being distracted by computing or mathematical issues.From simple NLMs to complex GLMMs and beyond, Bayesian Analysis Made Simple describes how to use Excel for a vast range of Bayesian models in an intuitive manner accessible to the statistically savvy user. Packed with relevant case studies, this book is for any data analyst wishing to apply Bayesian methods to analyze their data, from professional statisticians to statistically aware scientists" "Preface Although the popularity of the Bayesian approach to statistics has been growing rapidly for many years, among those working in business and industry there are still many who think of it as somewhat esoteric, not focused on practical issues, or generally quite difficult to understand. This view may be partly due to the relatively few books that focus primarily on how to apply Bayesian methods to a wide range of common problems. I believe that the essence of the approach is not only much more relevant to the scientific problems that require statistical thinking and methods, but also much easier to understand and explain to the wider scientific community. But being convinced of the benefits of the Bayesian approach is not enough if the person charged with analyzing the data does not have the computing software tools to implement these methods. Although WinBUGS (Lunn et al. 2000) provides sufficient functionality for the vast majority of data analyses that are undertaken, there is still a steep learning curve associated with the programming language that many will not have the time or motivation to overcome. This book describes a graphical user interface (GUI) for WinBUGS, BugsXLA, the purpose of which is to make Bayesian analysis relatively simple. Since I have always been an advocate of Excel as a tool for exploratory graphical analysis of data (somewhat against the antiExcel feelings in the statistical community generally), I created BugsXLA as an Excel addin. Other than to calculate some simple summary statistics from the data, Excel is only used as a convenient vehicle to store the data, plus some metadata used by BugsXLA, as well as a home for the Visual Basic program itself" Exemplaires (1)
Codebarres Cote Support Localisation Section DisponibilitÃ© 69108 WOO_11_69108 Livre Salle des ouvrages 11_Mathématiques Sorti jusqu'au 25/05/2043
Titre : Frailty models in survival analysis Type de document : livre Auteurs : Wienke, Andreas, Auteur Editeur : Boca Raton, Florida : CRC Press AnnÃ©e de publication : 2011 Collection : Chapman & Hall/CRC Biostatistics series Importance : 301 p. ISBN/ISSN/EAN : 9781420073881 Langues : Anglais (eng) MotsclÃ©s : Demography FAILURE TIME DATA ANALYSIS Mathematical models Mathematics MORTALITY Survival analysis (Biometry) RÃ©sumÃ© : "The concept of frailty offers a convenient way to introduce unobserved heterogeneity and associations into models for survival data. In its simplest form, frailty is an unobserved random proportionality factor that modifies the hazard function of an individual or a group of related individuals. Frailty Models in Survival Analysis presents a comprehensive overview of the fundamental approaches in the area of frailty models. The book extensively explores how univariate frailty models can represent unobserved heterogeneity. It also emphasizes correlated frailty models as extensions of univariate and shared frailty models. The author analyzes similarities and differences between frailty and copula models; discusses problems related to frailty models, such as tests for homogeneity; and describes parametric and semiparametric models using both frequentist and Bayesian approaches. He also shows how to apply the models to real data using the statistical packages of R, SAS, and Stata. The appendix provides the technical mathematical results used throughout. Written in nontechnical terms accessible to nonspecialists, this book explains the basic ideas in frailty modeling and statistical techniques, with a focus on realworld data application and interpretation of the results. By applying several models to the same data, it allows for the comparison of their advantages and limitations under varying model assumptions. The book also employs simulations to analyze the finite sample size performance of the models." En ligne : https://www.routledge.com/FrailtyModelsinSurvivalAnalysis/Wienke/p/book/9781 [...] Frailty models in survival analysis [livre] / Wienke, Andreas, Auteur .  Boca Raton, Florida : CRC Press, 2011 .  301 p..  (Chapman & Hall/CRC Biostatistics series) .
ISBN : 9781420073881
Langues : Anglais (eng)
MotsclÃ©s : Demography FAILURE TIME DATA ANALYSIS Mathematical models Mathematics MORTALITY Survival analysis (Biometry) RÃ©sumÃ© : "The concept of frailty offers a convenient way to introduce unobserved heterogeneity and associations into models for survival data. In its simplest form, frailty is an unobserved random proportionality factor that modifies the hazard function of an individual or a group of related individuals. Frailty Models in Survival Analysis presents a comprehensive overview of the fundamental approaches in the area of frailty models. The book extensively explores how univariate frailty models can represent unobserved heterogeneity. It also emphasizes correlated frailty models as extensions of univariate and shared frailty models. The author analyzes similarities and differences between frailty and copula models; discusses problems related to frailty models, such as tests for homogeneity; and describes parametric and semiparametric models using both frequentist and Bayesian approaches. He also shows how to apply the models to real data using the statistical packages of R, SAS, and Stata. The appendix provides the technical mathematical results used throughout. Written in nontechnical terms accessible to nonspecialists, this book explains the basic ideas in frailty modeling and statistical techniques, with a focus on realworld data application and interpretation of the results. By applying several models to the same data, it allows for the comparison of their advantages and limitations under varying model assumptions. The book also employs simulations to analyze the finite sample size performance of the models." En ligne : https://www.routledge.com/FrailtyModelsinSurvivalAnalysis/Wienke/p/book/9781 [...] Exemplaires (1)
Codebarres Cote Support Localisation Section DisponibilitÃ© 69091 WIE_11_69091 Livre Salle des ouvrages 11_Mathématiques Sorti jusqu'au 25/05/2043