{"product_id":"9783032192226","title":"Bayesian Regression and Causal Inference With Examples in R","description":"\u003ch1\u003eBayesian Regression and Causal Inference\u003c\/h1\u003e\u003ch2\u003eWith Examples in R\u003c\/h2\u003e\u003ch3\u003eDonlapark Ponnoprat\u003c\/h3\u003e\u003cdiv\u003e\u003cb\u003eMathematics \/ Probability \u0026amp; Statistics \/ Regression Analysis\u003c\/b\u003e\u003c\/div\u003e\u003cbr\u003e\u003cdiv\u003e\n\u003cp class=\"default\" style=\"mso-hyphenate: none; tab-stops: .5in 1.0in 1.5in 2.0in 2.5in 3.0in 3.5in 4.0in 4.5in 5.0in 390.0pt; margin: 0in 0in 12.0pt 0in;\"\u003e\u003cspan style=\"font-family: 'Times Roman',serif;\"\u003eThis textbook provides a practical guide to the Bayesian framework for data modeling and causal inference, focusing on model interpretation, diagnostics, and uncertainty quantification. Central to the book is a \"learning-by-doing\" approach, using concrete examples in \u003cstrong\u003eR\u003c\/strong\u003e with real-world datasets spanning diverse fields, including education, psychology, medicine, behavioral science, and environmental science.\u003c\/span\u003e\u003c\/p\u003e\r\n\u003cp class=\"default\" style=\"mso-hyphenate: none; tab-stops: .5in 1.0in 1.5in 2.0in 2.5in 3.0in 3.5in 4.0in 4.5in 5.0in 390.0pt; margin: 0in 0in 12.0pt 0in;\"\u003e\u003cspan style=\"font-family: 'Times Roman',serif;\"\u003eThe book is structured into three parts:\u003c\/span\u003e\u003c\/p\u003e\r\n\u003cp class=\"default\" style=\"text-indent: -.25in; mso-list: l0 level1 lfo1; mso-hyphenate: none; tab-stops: 1.0in 1.5in 2.0in 2.5in 3.0in 3.5in 4.0in 4.5in 5.0in 390.0pt; margin: 0in 0in 12.0pt .5in;\"\u003e\u003c!-- [if !supportLists]--\u003e\u003c!-- [if !supportLists]--\u003e\u003c!-- [if !supportLists]--\u003e\u003cspan style=\"font-family: Symbol; mso-fareast-font-family: Symbol; mso-bidi-font-family: Symbol;\"\u003e\u003cspan style=\"mso-list: Ignore;\"\u003e·\u003cspan style=\"font: 7.0pt 'Times New Roman';\"\u003e         \u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c!--[endif]--\u003e\u003cstrong\u003e\u003cspan style=\"font-family: 'Times Roman',serif;\"\u003ePart I: Linear \u003c\/span\u003e\u003c\/strong\u003e\u003cstrong\u003e\u003cspan lang=\"PT\" style=\"font-family: 'Times Roman',serif; mso-ansi-language: PT;\"\u003eRegression\u003c\/span\u003e\u003c\/strong\u003e\u003cspan style=\"font-family: 'Times Roman',serif;\"\u003e – Learn the basics of Bayesian linear regression, model diagnostics, and uncertainty quantification through a probabilistic lens.\u003c\/span\u003e\u003c\/p\u003e\r\n\u003cp class=\"default\" style=\"text-indent: -.25in; mso-list: l0 level1 lfo1; mso-hyphenate: none; tab-stops: 1.0in 1.5in 2.0in 2.5in 3.0in 3.5in 4.0in 4.5in 5.0in 390.0pt; margin: 0in 0in 12.0pt .5in;\"\u003e\u003c!-- [if !supportLists]--\u003e\u003c!-- [if !supportLists]--\u003e\u003c!-- [if !supportLists]--\u003e\u003cspan style=\"font-family: Symbol; mso-fareast-font-family: Symbol; mso-bidi-font-family: Symbol;\"\u003e\u003cspan style=\"mso-list: Ignore;\"\u003e·\u003cspan style=\"font: 7.0pt 'Times New Roman';\"\u003e         \u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c!--[endif]--\u003e\u003cstrong\u003e\u003cspan style=\"font-family: 'Times Roman',serif;\"\u003ePart II: Generalized Linear Models\u003c\/span\u003e\u003c\/strong\u003e\u003cspan style=\"font-family: 'Times Roman',serif;\"\u003e – Extend your modeling toolkit to handle binary and count data, zero-inflated models, and clustered data structures common in longitudinal studies.\u003c\/span\u003e\u003c\/p\u003e\r\n\u003cp class=\"default\" style=\"text-indent: -.25in; mso-list: l0 level1 lfo1; mso-hyphenate: none; tab-stops: 1.0in 1.5in 2.0in 2.5in 3.0in 3.5in 4.0in 4.5in 5.0in 390.0pt; margin: 0in 0in 12.0pt .5in;\"\u003e\u003c!-- [if !supportLists]--\u003e\u003c!-- [if !supportLists]--\u003e\u003c!-- [if !supportLists]--\u003e\u003cspan style=\"font-family: Symbol; mso-fareast-font-family: Symbol; mso-bidi-font-family: Symbol;\"\u003e\u003cspan style=\"mso-list: Ignore;\"\u003e·\u003cspan style=\"font: 7.0pt 'Times New Roman';\"\u003e         \u003c\/span\u003e\u003c\/span\u003e\u003c\/span\u003e\u003c!--[endif]--\u003e\u003cstrong\u003e\u003cspan style=\"font-family: 'Times Roman',serif;\"\u003ePart III: Causal Inference\u003c\/span\u003e\u003c\/strong\u003e\u003cspan style=\"font-family: 'Times Roman',serif;\"\u003e – Learn to identify treatment effects from non-experimental data. This section explores classical techniques—including inverse probability weighting, doubly robust estimation, instrumental variables, and difference-in-differences—alongside advanced techniques like synthetic control, doubly robust DiD, and synthetic DiD.\u003c\/span\u003e\u003c\/p\u003e\n\u003c\/div\u003e\u003cdiv\u003e\u003cp class=\"MsoPlainText\"\u003e\u003cstrong\u003eDonlapark Ponnoprat\u003c\/strong\u003e is a Lecturer in the Department of Statistics at \u003cspan style=\"color: #222222; background: white;\"\u003eChiang Mai University\u003c\/span\u003e, where he teaches courses on machine learning and statistics. His research focuses on developing novel methods for estimation and inference in high-dimensional data. He earned his bachelor's degrees in mathematics and economics from Brown University, and Ph.D. in mathematics from the University of California San Diego.\u003c\/p\u003e\u003c\/div\u003e\u003cbr\u003e\u003ctable\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublication Date: \u003c\/td\u003e\n\u003ctd\u003e26 August 2026\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePublisher: \u003c\/td\u003e\n\u003ctd\u003eSpringer Nature Switzerland\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eImprint: \u003c\/td\u003e\n\u003ctd\u003eSpringer\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eISBN-13: \u003c\/td\u003e\n\u003ctd\u003e9783032192226\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003eFormat: \u003c\/td\u003e\n\u003ctd\u003eHardback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd\u003ePage Count: \u003c\/td\u003e\n\u003ctd\u003e241\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/table\u003e","brand":"Springer Nature Switzerland","offers":[{"title":"Default Title","offer_id":46040648482956,"sku":"9783032192226","price":107.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0710\/9545\/1788\/files\/9783032192226.jpg?v=1780604180","url":"https:\/\/lateknightbooks.com\/products\/9783032192226","provider":"Late Knight Books and Services, LLC","version":"1.0","type":"link"}