Warehouse Stock Clearance Sale

Grab a bargain today!


Sign Up for Fishpond's Best Deals Delivered to You Every Day
Go
Regression Modeling for ­Linguistic Data

Rating
Format
Paperback, 454 pages
Published
United States, 1 June 2023

The 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.

The 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.

In 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. The book features extensive treatment of mixed-effects regression models, the most widely used statistical method for analyzing linguistic data.

Sonderegger 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.



The only advanced discussion of modeling for linguists
Uses R throughout, in practical examples using real datasets
Extensive treatment of mixed-effects regression models
Contains detailed, clear guidance on reporting models
Equal emphasis on observational data and data from controlled experiments
Suitable for graduate students and researchers with computational interests across linguistics and cognitive science

Show more

Our Price
£44.36
Elsewhere
£57.00
Save £12.64 (22%)
Ships from UK Estimated delivery date: 7th Feb - 11th Feb from UK

Buy Together
+
Buy together with Junos High Availability at a great price!
Buy Together
£77.75
Elsewhere Price
£100.35
You Save £22.60 (23%)

Product Description

The 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.

The 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.

In 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. The book features extensive treatment of mixed-effects regression models, the most widely used statistical method for analyzing linguistic data.

Sonderegger 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.



The only advanced discussion of modeling for linguists
Uses R throughout, in practical examples using real datasets
Extensive treatment of mixed-effects regression models
Contains detailed, clear guidance on reporting models
Equal emphasis on observational data and data from controlled experiments
Suitable for graduate students and researchers with computational interests across linguistics and cognitive science

Show more
Product Details
EAN
9780262045483
ISBN
0262045486
Publisher
Other Information
6 colour illustrations, 90 black and white illustrations
Dimensions
3.8 x 25.4 x 25.4 centimeters (0.37 kg)

Table of Contents

Preface xi
1 Preliminaries 1
2 Samples, Estimates, and Hypothesis Tests 7
3 Effect Size, Power, and Error 39
4 Linear Regression 1 69
5 Linear Regression 2 95
6 Categorical Data Analysis and Logistic Regression 147
7 Practical Regression Topics 191
8 Mixed-Effects Models 1: Linear Regression 241
9 Mixed-Effects Models 2: Logistic Regression 313
10 Mixed-Effects Models 3: Practical and Advanced Topics 357
A Appendix: Datasets 409
B Appendix: R Packages 411

About the Author

Morgan Sonderegger is Associate Professor of Linguistics at McGill University.

Show more
Review this Product
Ask a Question About this Product More...
 
Look for similar items by category
Item ships from and is sold by Fishpond World Ltd.

Back to top
We use essential and some optional cookies to provide you the best shopping experience. Visit our cookies policy page for more information.