{"product_id":"9780262045483","title":"Regression Modeling for Linguistic Data","description":"\u003ctable\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eAuthor\/Contributor(s):\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"\"\u003eSonderegger, Morgan\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003ePublisher:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003eThe MIT Press\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eDate:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e6\/6\/2023\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eBinding:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"\"\u003ePaperback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"\"\u003eNEW\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e\u003cb\u003eThe first comprehensive textbook on regression modeling for linguistic data offers an incisive conceptual overview along with worked examples that teach practical skills for realistic data analysis.\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003eIn the first comprehensive textbook on regression modeling for linguistic data in a frequentist framework, Morgan Sonderegger provides graduate students and researchers with an incisive conceptual overview along with worked examples that teach practical skills for realistic data analysis\u003ci\u003e.\u003c\/i\u003e The book features extensive treatment of mixed-effects regression models, the most widely used statistical method for analyzing linguistic data. \u003cbr\u003e\u003cbr\u003eSonderegger begins with preliminaries to regression modeling: assumptions, inferential statistics, hypothesis testing, power, and other errors. He then covers regression models for non-clustered data: linear regression, model selection and validation, logistic regression, and applied topics such as contrast coding and nonlinear effects. The last three chapters discuss regression models for clustered data: linear and logistic mixed-effects models as well as model predictions, convergence, and model selection. The book’s focused scope and practical emphasis will equip readers to implement these methods and understand how they are used in current work.\u003cbr\u003e\u003cbr\u003e\u003cul\u003e\n\u003cli\u003eThe only advanced discussion of modeling for linguists\u003c\/li\u003e\n\u003cli\u003eUses R throughout, in practical examples using real datasets\u003c\/li\u003e\n\u003cli\u003eExtensive treatment of mixed-effects regression models\u003c\/li\u003e\n\u003cli\u003eContains detailed, clear guidance on reporting models\u003c\/li\u003e\n\u003cli\u003eEqual emphasis on observational data and data from controlled experiments\u003c\/li\u003e\n\u003cli\u003eSuitable for graduate students and researchers with computational interests across linguistics and cognitive science\u003c\/li\u003e\n\u003c\/ul\u003e","brand":"The MIT Press","offers":[{"title":"Default Title","offer_id":44214511304959,"sku":"9780262045483","price":60.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0452\/0886\/2873\/files\/9780262045483_s600x595.jpg?v=1775601950","url":"https:\/\/massivebookshop.com\/de\/products\/9780262045483","provider":"MASSIVE BOOKSHOP","version":"1.0","type":"link"}