{"product_id":"regression-modeling-for-linguistic-data-isbn-9780262045483","title":"Regression Modeling for Linguistic Data","description":"\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\u003ePreface xi\u003cbr\u003e1 Preliminaries 1\u003cbr\u003e2 Samples, Estimates, and Hypothesis Tests 7\u003cbr\u003e3 Effect Size, Power, and Error 39\u003cbr\u003e4 Linear Regression 1 69\u003cbr\u003e5 Linear Regression 2 95\u003cbr\u003e6 Categorical Data Analysis and Logistic Regression 147\u003cbr\u003e7 Practical Regression Topics 191\u003cbr\u003e8 Mixed-Effects Models 1: Linear Regression 241\u003cbr\u003e9 Mixed-Effects Models 2: Logistic Regression 313\u003cbr\u003e10 Mixed-Effects Models 3: Practical and Advanced Topics 357\u003cbr\u003eA Appendix: Datasets 409\u003cbr\u003eB Appendix: R Packages 411\u003cb\u003eMorgan Sonderegger\u003c\/b\u003e is Associate Professor of Linguistics at McGill University.","brand":"The MIT Press","offers":[{"title":"Default Title","offer_id":46304162054373,"sku":"NP9780262045483","price":60.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9780262045483.jpg?v=1767735581","url":"https:\/\/k12savings.com\/products\/regression-modeling-for-linguistic-data-isbn-9780262045483","provider":"K12savings","version":"1.0","type":"link"}