Applied Bayesian Modelling (Hardcover)

Peter Congdon

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Description

The use of Bayesian statistics has grown significantly in recent years, and will undoubtedly continue to do so. Applied Bayesian Modelling is the follow-up to the author’s best selling book, Bayesian Statistical Modelling, and focuses on the potential applications of Bayesian techniques in a wide range of important topics in the social and health sciences. The applications are illustrated through many real-life examples and software implementation in WINBUGS – a popular software package that offers a simplified and flexible approach to statistical modelling. The book gives detailed explanations for each example – explaining fully the choice of model for each particular problem. The book

· Provides a broad and comprehensive account of applied Bayesian modelling.

· Describes a variety of model assessment methods and the flexibility of Bayesian prior specifications.

· Covers many application areas, including panel data models, structural equation and other multivariate structure models, spatial analysis, survival analysis and epidemiology.

· Provides detailed worked examples in WINBUGS to illustrate the practical application of the techniques described. All WINBUGS programs are available from an ftp site.

The book provides a good introduction to Bayesian modelling and data analysis for a wide range of people involved in applied statistical analysis, including researchers and students from statistics, and the health and social sciences. The wealth of examples makes this book an ideal reference for anyone involved in statistical modelling and analysis.

 

 

Table of contents

Preface.

The Basis for, and Advantages of, Bayesian Model Estimation via Repeated Sampling.

Hierarchical Mixture Models.

Regression Models.

Analysis of Multi-Level Data.

Models for Time Series.

Analysis of Panel Data.

Models for Spatial Outcomes and Geographical Association.

Structural Equation and Latent Variable Models.

Survival and Event History Models.

Modelling and Establishing Causal Relations: Epidemiological Methods and Models.

Index.

商品描述(中文翻譯)

描述

貝葉斯統計的應用在近年來顯著增長,並且無疑將繼續增長。《應用貝葉斯建模》是作者暢銷書《貝葉斯統計建模》的續集,專注於貝葉斯技術在社會和健康科學的各種重要主題中的潛在應用。這些應用通過許多實際例子和WINBUGS軟件實現來進行演示,WINBUGS是一個流行的軟件包,提供了簡化和靈活的統計建模方法。該書對每個例子都提供了詳細的解釋,完全解釋了每個特定問題的模型選擇。該書還提供了以下內容:

- 提供了廣泛而全面的應用貝葉斯建模介紹。
- 描述了各種模型評估方法和貝葉斯先驗規範的靈活性。
- 涵蓋了許多應用領域,包括面板數據模型、結構方程和其他多變量結構模型、空間分析、生存分析和流行病學。
- 提供了WINBUGS中詳細的實例,以說明所描述技術的實際應用。所有WINBUGS程序都可以從ftp站點上獲得。

該書為從事應用統計分析的各種人士提供了對貝葉斯建模和數據分析的良好介紹,包括統計學、健康科學和社會科學的研究人員和學生。豐富的例子使該書成為從事統計建模和分析的人士的理想參考書。

目錄

前言
通過重複抽樣進行貝葉斯模型估計的基礎和優勢
階層混合模型
回歸模型
多層次數據分析
時間序列模型