LEADER 03551oam 2200613I 450 001 9910781932303321 005 20230802004254.0 010 $a0-429-15195-0 010 $a1-283-35030-0 010 $a9786613350305 010 $a1-4398-3955-7 024 7 $a10.1201/b11235 035 $a(CKB)2550000000063558 035 $a(EBL)800928 035 $a(OCoLC)763161378 035 $a(SSID)ssj0000564978 035 $a(PQKBManifestationID)11354481 035 $a(PQKBTitleCode)TC0000564978 035 $a(PQKBWorkID)10527809 035 $a(PQKB)10687724 035 $a(MiAaPQ)EBC800928 035 $a(Au-PeEL)EBL800928 035 $a(CaPaEBR)ebr10508902 035 $a(CaONFJC)MIL335030 035 $a(EXLCZ)992550000000063558 100 $a20180331d2012 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aBayesian analysis made simple $ean Excel GUI for WinBUGS /$fPhil Woodward 210 1$aBoca Raton, Fla. :$cCRC Press,$d2012. 215 $a1 online resource (364 p.) 225 1 $aChapman & Hall/CRC biostatistics series 300 $aA Chapman & Hall book. 311 $a1-4398-3954-9 320 $aIncludes bibliographical references. 327 $aFront Cover; Contents; Case Studies; Preface; Acknowledgments; Chapter 1: Brief Introduction to Statistics, Bayesian Methods, and WinBUGS; Chapter 2: BugsXLA Overview and Reference Manual; Chapter 3: Normal Linear Models; Chapter 4: Generalized Linear Models; Chapter 5: Normal Linear Mixed Models; Chapter 6: Generalized Linear Mixed Models; Chapter 7: Emax or Four-Parameter Logistic Non-Linear Models; Chapter 8: Bayesian Variable Selection; Chapter 9: Longitudinal and Repeated Measures Models; Chapter 10: Robust Models; Chapter 11: Beyond BugsXLA: Extending the WinBUGS Code 327 $aAppendix A: Distributions Referenced in BugsXLAAppendix E: Troubleshooting; References; Back Cover 330 $aAlthough the popularity of the Bayesian approach to statistics has been growing for years, many still think of it as somewhat esoteric, not focused on practical issues, or generally too difficult to understand.Bayesian Analysis Made Simple is aimed at those who wish to apply Bayesian methods but either are not experts or do not have the time to create WinBUGS code and ancillary files for every analysis they undertake. Accessible to even those who would not routinely use Excel, this book provides a custom-made Excel GUI, immediately useful to those users who want to be able to quickly apply Bayesian methods without being distracted by computing or mathematical issues.From simple NLMs to complex GLMMs and beyond, Bayesian Analysis Made Simple describes how to use Excel for a vast range of Bayesian models in an intuitive manner accessible to the statistically savvy user. Packed with relevant case studies, this book is for any data analyst wishing to apply Bayesian methods to analyze their data, from professional statisticians to statistically aware scientists--$cProvided by publisher. 410 0$aChapman & Hall/CRC biostatistics series (Unnumbered) 606 $aBayesian statistical decision theory 615 0$aBayesian statistical decision theory. 676 $a519.5/42028553 686 $aMAT029000$2bisacsh 700 $aWoodward$b Phillip.$01527824 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910781932303321 996 $aBayesian analysis made simple$93771061 997 $aUNINA