Bayesian Analysis Made Simple : An Excel GUI for WinBUGS

Content: Brief Introduction to Statistics, Bayesian Methods, and WinBUGS Bayesian Paradigm WinBUGS Why Bother Using Bayesian Methods? BugsXLA Overview and Reference Manual Downloading and Installing BugsXLA BugsXLA Toolbar Bayesian Model Specification Set Variable Types MCMC & Output Options Predictions and Contrasts Prior Distributions Graphical Feedback Interface Model Checks Import Results Posterior Plots BugsXLA Options WinBUGS Utilities Normal Linear Models Generalized Linear Models Binomial Data Poisson Data Survival or Reliability Data Multivariate Categorical Data Normal Linear Mixed Models Generalized Linear Mixed Models Emax or Four-Parameter Logistic Non-Linear Models Bayesian Variable Selection Longitudinal and Repeated Measures Models Robust Models Beyond BugsXLA: Extending the WinBUGS Code Using BugsXLA's WinBUGS Utilities Editing the Initial MCMC Values Estimating Additional Quantities of Interest Appendix A: Distributions Referenced in BugsXLA Appendix B: BugsXLA's Automatically Generated Initial Values Appendix C: Explanation of WinBUGS Code Created by BugsXLA Appendix D: Explanation of R Scripts Created by BugsXLA Appendix E: Troubleshooting References Index
Abstract: From simple NLMs to complex GLMMs, this book describes how to use the GUI for WinBUGS - BugsXLA - an Excel add-in written by the author that allows a range of Bayesian models to be easily specified. With case studies throughout, the text shows how to routinely apply even the more complex aspects of model specification, such as GLMMs, outlier robust models, random effects Emax models, auto-regressive errors, and Bayesian variable selection. It provides brief, up-to-date discussions of current issues in the practical application of Bayesian methods. The author also explains how to obtain free so