Regression Modeling For Linguistic Data
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Regression Modeling For Linguistic Data
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Author : Morgan Sonderegger
language : en
Publisher: MIT Press
Release Date : 2023-06-06
Regression Modeling For Linguistic Data written by Morgan Sonderegger and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-06 with Science categories.
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
Mixed Effects Regression Models In Linguistics
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Author : Dirk Speelman
language : en
Publisher: Springer
Release Date : 2018-02-07
Mixed Effects Regression Models In Linguistics written by Dirk Speelman and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-07 with Social Science categories.
When data consist of grouped observations or clusters, and there is a risk that measurements within the same group are not independent, group-specific random effects can be added to a regression model in order to account for such within-group associations. Regression models that contain such group-specific random effects are called mixed-effects regression models, or simply mixed models. Mixed models are a versatile tool that can handle both balanced and unbalanced datasets and that can also be applied when several layers of grouping are present in the data; these layers can either be nested or crossed. In linguistics, as in many other fields, the use of mixed models has gained ground rapidly over the last decade. This methodological evolution enables us to build more sophisticated and arguably more realistic models, but, due to its technical complexity, also introduces new challenges. This volume brings together a number of promising new evolutions in the use of mixed models in linguistics, but also addresses a number of common complications, misunderstandings, and pitfalls. Topics that are covered include the use of huge datasets, dealing with non-linear relations, issues of cross-validation, and issues of model selection and complex random structures. The volume features examples from various subfields in linguistics. The book also provides R code for a wide range of analyses.
How To Do Linguistics With R
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Author : Natalia Levshina
language : en
Publisher: John Benjamins Publishing Company
Release Date : 2015-11-25
How To Do Linguistics With R written by Natalia Levshina and has been published by John Benjamins Publishing Company this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-25 with Language Arts & Disciplines categories.
This book provides a linguist with a statistical toolkit for exploration and analysis of linguistic data. It employs R, a free software environment for statistical computing, which is increasingly popular among linguists. How to do Linguistics with R: Data exploration and statistical analysis is unique in its scope, as it covers a wide range of classical and cutting-edge statistical methods, including different flavours of regression analysis and ANOVA, random forests and conditional inference trees, as well as specific linguistic approaches, among which are Behavioural Profiles, Vector Space Models and various measures of association between words and constructions. The statistical topics are presented comprehensively, but without too much technical detail, and illustrated with linguistic case studies that answer non-trivial research questions. The book also demonstrates how to visualize linguistic data with the help of attractive informative graphs, including the popular ggplot2 system and Google visualization tools. This book has a companion website: http://doi.org/10.1075/z.195.website
Analyzing Linguistic Data
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Author : R. H. Baayen
language : en
Publisher: Cambridge University Press
Release Date : 2008-03-06
Analyzing Linguistic Data written by R. H. Baayen and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-03-06 with Language Arts & Disciplines categories.
Statistical analysis is a useful skill for linguists and psycholinguists, allowing them to understand the quantitative structure of their data. This textbook provides a straightforward introduction to the statistical analysis of language. Designed for linguists with a non-mathematical background, it clearly introduces the basic principles and methods of statistical analysis, using 'R', the leading computational statistics programme. The reader is guided step-by-step through a range of real data sets, allowing them to analyse acoustic data, construct grammatical trees for a variety of languages, quantify register variation in corpus linguistics, and measure experimental data using state-of-the-art models. The visualization of data plays a key role, both in the initial stages of data exploration and later on when the reader is encouraged to criticize various models. Containing over 40 exercises with model answers, this book will be welcomed by all linguists wishing to learn more about working with and presenting quantitative data.
Mixed Effects Regression Models In Linguistics
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Author : Dirk Speelman
language : en
Publisher:
Release Date : 2018
Mixed Effects Regression Models In Linguistics written by Dirk Speelman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Grammar, Comparative and general categories.
When data consist of grouped observations or clusters, and there is a risk that measurements within the same group are not independent, group-specific random effects can be added to a regression model in order to account for such within-group associations. Regression models that contain such group-specific random effects are called mixed-effects regression models, or simply mixed models. Mixed models are a versatile tool that can handle both balanced and unbalanced datasets and that can also be applied when several layers of grouping are present in the data; these layers can either be nested or crossed. In linguistics, as in many other fields, the use of mixed models has gained ground rapidly over the last decade. This methodological evolution enables us to build more sophisticated and arguably more realistic models, but, due to its technical complexity, also introduces new challenges. This volume brings together a number of promising new evolutions in the use of mixed models in linguistics, but also addresses a number of common complications, misunderstandings, and pitfalls. Topics that are covered include the use of huge datasets, dealing with non-linear relations, issues of cross-validation, and issues of model selection and complex random structures. The volume features examples from various subfields in linguistics. The book also provides R code for a wide range of analyses.
Analyzing Linguistic Data
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Author : Harald Baayen
language : en
Publisher:
Release Date : 2008
Analyzing Linguistic Data written by Harald Baayen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Linguistics categories.
A straightforward introduction to the statistical analysis of language data, designed for students with a non-mathematical background.
Statistics For Linguistics With R
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Author : Stefan Th. Gries
language : en
Publisher: Walter de Gruyter
Release Date : 2013-03-22
Statistics For Linguistics With R written by Stefan Th. Gries and has been published by Walter de Gruyter this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-22 with Language Arts & Disciplines categories.
This book is the revised and extended second edition of Statistics for Linguistics with R. The volume is an introduction to statistics for linguists using the open source software R. It is aimed at students and instructors/professors with little or no statistical background and is written in a non-technical and reader-friendly/accessible style. It first introduces in detail the overall logic underlying quantitative studies: exploration, hypothesis formulation and operationalization, and the notion and meaning of significance tests. It then introduces some basics of the software R relevant to statistical data analysis. A chapter on descriptive statistics explains how summary statistics for frequencies, averages, and correlations are generated with R and how they are graphically represented best. A chapter on analytical statistics explains how statistical tests are performed in R on the basis of many different linguistic case studies: For nearly every single example, it is explained what the structure of the test looks like, how hypotheses are formulated, explored, and tested for statistical significance, how the results are graphically represented, and how one would summarize them in a paper/article. A chapter on selected multifactorial methods introduces how more complex research designs can be studied: methods for the study of multifactorial frequency data, correlations, tests for means, and binary response data are discussed and exemplified step-by-step. Also, the exploratory approach of hierarchical cluster analysis is illustrated in detail. The book comes with many exercises, boxes with short think breaks and warnings, recommendations for further study, and answer keys as well as a statistics for linguists newsgroup on the companion website. Just like the first edition, it is aimed at students, faculty, and researchers with little or no statistical background in statistics or the open source programming language R. It avoids mathematical jargon and discusses the logic and structure of quantitative studies and introduces descriptive statistics as well as a range of monofactorial statistical tests for frequencies, distributions, means, dispersions, and correlations. The comprehensive revision includes new small sections on programming topics that facilitate statistical analysis, the addition of a variety of statistical functions readers can apply to their own data, a revision of overview sections on statistical tests and regression modeling, a complete rewrite of the chapter on multifactorial approaches, which now contains sections on linear regression, binary and ordinal logistic regression, multinomial and Poisson regression, and repeated-measures ANOVA, and a new visual tool to identify the right statistical test for a given problem and data set. The amount of code available from the companion website has doubled in size, providing much supplementary material on statistical tests and advanced plotting.
Statistics For Linguistics With R
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Author : Stefan Th. Gries
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2021-05-10
Statistics For Linguistics With R written by Stefan Th. Gries and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-10 with Language Arts & Disciplines categories.
This is the third, newly revised and extended edition of this successful book (that has already been translated into three languages). Like the previous editions, it is entirely based on the programming language and environment R and is still thoroughly hands-on (with thousands of lines of heavily annotated code for all computations and plots). However, this edition has been updated based on many workshops/bootcamps taught by the author all over the world for the past few years: This edition has been didactically streamlined with regard to its exposition, it adds two new chapters – one on mixed-effects modeling, one on classification and regression trees as well as random forests – plus it features new discussion of curvature, orthogonal and other contrasts, interactions, collinearity, the effects and emmeans packages, autocorrelation/runs, some more bits on programming, writing statistical functions, and simulations, and many practical tips based on 10 years of teaching with these materials.
Data Visualization And Analysis In Second Language Research
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Author : Guilherme D. Garcia
language : en
Publisher: Taylor & Francis
Release Date : 2021-05-30
Data Visualization And Analysis In Second Language Research written by Guilherme D. Garcia and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-30 with Business & Economics categories.
This introduction to visualization techniques and statistical models for second language research focuses on three types of data (continuous, binary, and scalar), helping readers to understand regression models fully and to apply them in their work. Garcia offers advanced coverage of Bayesian analysis, simulated data, exercises, implementable script code, and practical guidance on the latest R software packages. The book, also demonstrating the benefits to the L2 field of this type of statistical work, is a resource for graduate students and researchers in second language acquisition, applied linguistics, and corpus linguistics who are interested in quantitative data analysis.
Analyzing Linguistic Data Electronic Resource
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Author : R. Harald Baayen
language : en
Publisher:
Release Date : 2008
Analyzing Linguistic Data Electronic Resource written by R. Harald Baayen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.