{"id":565,"date":"2019-01-02T12:24:30","date_gmt":"2019-01-02T12:24:30","guid":{"rendered":"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/?post_type=chapter&#038;p=565"},"modified":"2019-01-02T12:24:30","modified_gmt":"2019-01-02T12:24:30","slug":"missing-data-models","status":"publish","type":"chapter","link":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/chapter\/missing-data-models\/","title":{"rendered":"Missing Data Models"},"content":{"raw":"<img class=\"aligncenter size-full wp-image-566\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_06.jpg\" alt=\"\" width=\"1509\" height=\"673\" \/> <img class=\"aligncenter size-full wp-image-567\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_09.jpg\" alt=\"\" width=\"1511\" height=\"891\" \/> <img class=\"aligncenter size-full wp-image-568\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_11.jpg\" alt=\"\" width=\"1511\" height=\"441\" \/> <img class=\"aligncenter size-full wp-image-569\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_16.jpg\" alt=\"\" width=\"1512\" height=\"1076\" \/> <img class=\"aligncenter size-full wp-image-570\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_18.jpg\" alt=\"\" width=\"1503\" height=\"565\" \/> <img class=\"aligncenter size-full wp-image-571\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_23.jpg\" alt=\"\" width=\"1512\" height=\"1102\" \/> <img class=\"aligncenter size-full wp-image-572\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_28.jpg\" alt=\"\" width=\"1509\" height=\"974\" \/> <img class=\"aligncenter size-full wp-image-573\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_32.jpg\" alt=\"\" width=\"1511\" height=\"971\" \/> <img class=\"aligncenter size-full wp-image-574\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_36.jpg\" alt=\"\" width=\"1512\" height=\"1102\" \/> <img class=\"aligncenter size-full wp-image-575\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_39.jpg\" alt=\"\" width=\"1512\" height=\"1106\" \/> <img class=\"aligncenter size-full wp-image-576\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_41.jpg\" alt=\"\" width=\"1509\" height=\"539\" \/> <img class=\"aligncenter size-full wp-image-577\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_44.jpg\" alt=\"\" width=\"1512\" height=\"1097\" \/> <img class=\"aligncenter size-full wp-image-578\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_46.jpg\" alt=\"\" width=\"1507\" height=\"825\" \/> <img class=\"aligncenter size-full wp-image-579\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_48.jpg\" alt=\"\" width=\"1511\" height=\"581\" \/> <img class=\"aligncenter size-full wp-image-580\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_52.jpg\" alt=\"\" width=\"1509\" height=\"971\" \/> <img class=\"aligncenter size-full wp-image-581\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_55.jpg\" alt=\"\" width=\"1511\" height=\"893\" \/> <img class=\"aligncenter wp-image-582 size-full\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_58-e1546431709241.jpg\" alt=\"\" width=\"1509\" height=\"860\" \/> <img class=\"aligncenter wp-image-583 size-full\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_59-e1546431727396.jpg\" alt=\"\" width=\"1510\" height=\"683\" \/> <img class=\"aligncenter size-full wp-image-584\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_62.jpg\" alt=\"\" width=\"1511\" height=\"789\" \/> <img class=\"aligncenter size-full wp-image-585\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_65.jpg\" alt=\"\" width=\"1511\" height=\"617\" \/> <img class=\"aligncenter size-full wp-image-586\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_68.jpg\" alt=\"\" width=\"1509\" height=\"635\" \/> <img class=\"aligncenter size-full wp-image-587\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_72.jpg\" alt=\"\" width=\"1509\" height=\"783\" \/> <img class=\"aligncenter size-full wp-image-588\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_73.jpg\" alt=\"\" width=\"1510\" height=\"988\" \/> <img class=\"aligncenter size-full wp-image-589\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_74.jpg\" alt=\"\" width=\"1512\" height=\"1110\" \/> <img class=\"aligncenter size-full wp-image-590\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_75.jpg\" alt=\"\" width=\"1511\" height=\"915\" \/> <img class=\"aligncenter size-full wp-image-591\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_76.jpg\" alt=\"\" width=\"1509\" height=\"903\" \/> <img class=\"aligncenter size-full wp-image-592\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_77.jpg\" alt=\"\" width=\"1509\" height=\"905\" \/> <img class=\"aligncenter size-full wp-image-593\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_78.jpg\" alt=\"\" width=\"1511\" height=\"907\" \/> <img class=\"aligncenter size-full wp-image-594\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_79.jpg\" alt=\"\" width=\"1511\" height=\"905\" \/>\r\n\r\n&nbsp;\r\n\r\n<strong>Reference<\/strong>\r\n<ol>\r\n \t<li>Beayesian Data Analysis\u201d, 3rd Edition, By Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari and Donald B. Rubin.<\/li>\r\n \t<li>Bayesian Statistics: An Introduction\u201d, By Peter Lee, 4th Edition, ISBN: 978-1-118-33257-3.<\/li>\r\n \t<li>Monte Carlo Statistical Methods, By Robert, Christian P. andGeorge Casella. 2004. , 2nd edition. Springer.<\/li>\r\n \t<li>MCMCpack: Markov Chain Monte Carlo in R.\u201d, (2011), Andrew D. Martin, Kevin M. Quinn, and Jong HeePark,Journal of Statistical Software. 42(9): 1-21.<\/li>\r\n \t<li>Applied Bayesian Modeling\u201d By Peter Congdon, 2nd Edition,Wiley,. ISBN: 978-1-119-95151-3<\/li>\r\n \t<li>Bayes Linear Statistics, Theory Methods\u201d. By Goldstein,Michael; Woo, David (2007). Wiley. ISBN978-0-470-01562-9.<\/li>\r\n \t<li>Hosmer, D.W. and Lemeshow, S. (1989) Applied LogisticRegression. New York: Wiley.<\/li>\r\n \t<li>Venables, W. N. and Ripley, B. D. (2002) Modern AppliedStatistics with S. Fourth edition. Springer.<\/li>\r\n \t<li>Albert, J. H. and S. Chib. 1993. \\Bayesian Analysis of Binaryand Polychotomous Response Data.\u201dJ. Amer. Statist. Assoc.88, 669-679.<\/li>\r\n \t<li>Albert, J. H. and S. Chib. 1995. \\Bayesian Residual Analysisfor Binary Response Regression Models.\u201d Biometrika. 82,747-759.<\/li>\r\n \t<li>Andrew D. Martin, Kevin M. Quinn, and Jong Hee Park.2011. \u201cMCMCpack: Markov Chain Monte Carlo in R.\u201d,Journal of Statistical Software. 42(9): 1-21.http:\/\/www.jstatsoft.org\/v42\/i09\/I<\/li>\r\n \t<li>Siddhartha Chib. 1995. \\Marginal Likelihood from the GibbsOutput.\u201dJournal of the American Statistical Association.90:1313-1321.<\/li>\r\n \t<li>\r\n<div>Peter E. Rossi, Greg M. Allenby and Rob McCulloch, Bayesian Statistics and Marketing (2005), Wiley-Interscience, New York, NY.<\/div><\/li>\r\n \t<li>Adelino F. da Silva, cudaBayesreg: Bayesian Computation inCUDA (2010), The R Journal, Vol. 2\/2, 48-55.http:\/\/journal.r-project.org\/archive\/2010-2\/RJournal_2010-2_FerreiradaSilva.pdf<\/li>\r\n \t<li>King, Gary, James Honaker, Anne Joseph and KennethScheve. 2001. \\Analyzing incomplete political science data:An alternative algorithm for multiple imputation.\"AmericanPolitical Science Review95(1, March):49{69.http:\/\/gking.harvard.edu\/files\/abs\/evil-abs.shtml.<\/li>\r\n \t<li>King, Gary, Michael Tomz and Jason Wittenberg. 2000.\\Making the most of statistical analyses: Improvinginterpretation and presentation.\"American Journal of PoliticalScience44(2, April):341{355.http:\/\/gking.harvard.edu\/files\/abs\/making-abs.shtml.<\/li>\r\n \t<li>Honaker, James, Anne Joseph, Gary King, Kenneth Scheveand Nau- nihal Singh. 1998-2002. \\AMELIA: A program formissing data\".http:\/\/gking.harvard.edu\/amelia.<\/li>\r\n<\/ol>","rendered":"<p><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-566\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_06.jpg\" alt=\"\" width=\"1509\" height=\"673\" srcset=\"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_06.jpg 1509w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_06-300x134.jpg 300w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_06-768x343.jpg 768w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_06-1024x457.jpg 1024w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_06-65x29.jpg 65w, 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src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_78.jpg\" alt=\"\" width=\"1511\" height=\"907\" srcset=\"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_78.jpg 1511w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_78-300x180.jpg 300w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_78-768x461.jpg 768w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_78-1024x615.jpg 1024w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_78-65x39.jpg 65w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_78-225x135.jpg 225w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_78-350x210.jpg 350w\" sizes=\"auto, (max-width: 1511px) 100vw, 1511px\" \/> <img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-594\" src=\"http:\/\/statp06.epgpbooks.inflibnet.ac.in\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_79.jpg\" alt=\"\" width=\"1511\" height=\"905\" srcset=\"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_79.jpg 1511w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_79-300x180.jpg 300w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_79-768x460.jpg 768w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_79-1024x613.jpg 1024w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_79-65x39.jpg 65w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_79-225x135.jpg 225w, https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-content\/uploads\/sites\/133\/2019\/01\/1522660891Bayes_M18_Page_79-350x210.jpg 350w\" sizes=\"auto, (max-width: 1511px) 100vw, 1511px\" \/><\/p>\n<p>&nbsp;<\/p>\n<p><strong>Reference<\/strong><\/p>\n<ol>\n<li>Beayesian Data Analysis\u201d, 3rd Edition, By Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari and Donald B. Rubin.<\/li>\n<li>Bayesian Statistics: An Introduction\u201d, By Peter Lee, 4th Edition, ISBN: 978-1-118-33257-3.<\/li>\n<li>Monte Carlo Statistical Methods, By Robert, Christian P. andGeorge Casella. 2004. , 2nd edition. Springer.<\/li>\n<li>MCMCpack: Markov Chain Monte Carlo in R.\u201d, (2011), Andrew D. Martin, Kevin M. Quinn, and Jong HeePark,Journal of Statistical Software. 42(9): 1-21.<\/li>\n<li>Applied Bayesian Modeling\u201d By Peter Congdon, 2nd Edition,Wiley,. ISBN: 978-1-119-95151-3<\/li>\n<li>Bayes Linear Statistics, Theory Methods\u201d. By Goldstein,Michael; Woo, David (2007). Wiley. ISBN978-0-470-01562-9.<\/li>\n<li>Hosmer, D.W. and Lemeshow, S. (1989) Applied LogisticRegression. New York: Wiley.<\/li>\n<li>Venables, W. N. and Ripley, B. D. (2002) Modern AppliedStatistics with S. Fourth edition. Springer.<\/li>\n<li>Albert, J. H. and S. Chib. 1993. \\Bayesian Analysis of Binaryand Polychotomous Response Data.\u201dJ. Amer. Statist. Assoc.88, 669-679.<\/li>\n<li>Albert, J. H. and S. Chib. 1995. \\Bayesian Residual Analysisfor Binary Response Regression Models.\u201d Biometrika. 82,747-759.<\/li>\n<li>Andrew D. Martin, Kevin M. Quinn, and Jong Hee Park.2011. \u201cMCMCpack: Markov Chain Monte Carlo in R.\u201d,Journal of Statistical Software. 42(9): 1-21.http:\/\/www.jstatsoft.org\/v42\/i09\/I<\/li>\n<li>Siddhartha Chib. 1995. \\Marginal Likelihood from the GibbsOutput.\u201dJournal of the American Statistical Association.90:1313-1321.<\/li>\n<li>\n<div>Peter E. Rossi, Greg M. Allenby and Rob McCulloch, Bayesian Statistics and Marketing (2005), Wiley-Interscience, New York, NY.<\/div>\n<\/li>\n<li>Adelino F. da Silva, cudaBayesreg: Bayesian Computation inCUDA (2010), The R Journal, Vol. 2\/2, 48-55.http:\/\/journal.r-project.org\/archive\/2010-2\/RJournal_2010-2_FerreiradaSilva.pdf<\/li>\n<li>King, Gary, James Honaker, Anne Joseph and KennethScheve. 2001. \\Analyzing incomplete political science data:An alternative algorithm for multiple imputation.&#8221;AmericanPolitical Science Review95(1, March):49{69.http:\/\/gking.harvard.edu\/files\/abs\/evil-abs.shtml.<\/li>\n<li>King, Gary, Michael Tomz and Jason Wittenberg. 2000.\\Making the most of statistical analyses: Improvinginterpretation and presentation.&#8221;American Journal of PoliticalScience44(2, April):341{355.http:\/\/gking.harvard.edu\/files\/abs\/making-abs.shtml.<\/li>\n<li>Honaker, James, Anne Joseph, Gary King, Kenneth Scheveand Nau- nihal Singh. 1998-2002. \\AMELIA: A program formissing data&#8221;.http:\/\/gking.harvard.edu\/amelia.<\/li>\n<\/ol>\n","protected":false},"author":4,"menu_order":18,"template":"","meta":{"pb_show_title":"on","pb_short_title":"","pb_subtitle":"","pb_authors":["dr-sourish-das"],"pb_section_license":""},"chapter-type":[],"contributor":[58],"license":[],"class_list":["post-565","chapter","type-chapter","status-publish","hentry","contributor-dr-sourish-das"],"part":3,"_links":{"self":[{"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/pressbooks\/v2\/chapters\/565","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/pressbooks\/v2\/chapters"}],"about":[{"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/wp\/v2\/types\/chapter"}],"author":[{"embeddable":true,"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/wp\/v2\/users\/4"}],"version-history":[{"count":1,"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/pressbooks\/v2\/chapters\/565\/revisions"}],"predecessor-version":[{"id":595,"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/pressbooks\/v2\/chapters\/565\/revisions\/595"}],"part":[{"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/pressbooks\/v2\/parts\/3"}],"metadata":[{"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/pressbooks\/v2\/chapters\/565\/metadata\/"}],"wp:attachment":[{"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/wp\/v2\/media?parent=565"}],"wp:term":[{"taxonomy":"chapter-type","embeddable":true,"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/pressbooks\/v2\/chapter-type?post=565"},{"taxonomy":"contributor","embeddable":true,"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/wp\/v2\/contributor?post=565"},{"taxonomy":"license","embeddable":true,"href":"https:\/\/ebooks.inflibnet.ac.in\/statp06\/wp-json\/wp\/v2\/license?post=565"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}