Data and Methods in Corpus Linguistics - Title page

pp iii-iii

Copyright page

pp iv-iv

Contents

pp v-vi

Figures

pp vii-xi

Tables

pp xii-xiv

Contributors

pp xv-xv

Acknowledgements

pp xvi-xvi

Introduction: - Comparative Approaches to Data and Methods in Corpus Linguistics

pp 1-14

Part I - Corpus Dimensions and the Viability of Methodological Approaches

pp 15-72

1 - Comparing Standard Reference Corpora and Google Books Ngrams

pp 17-45

2 - Comparing Approaches to Phonological and Orthographic Corpus Formats

pp 46-72

Part II - Selection, Calibration and Preparation of Corpus Data

pp 73-160

3 - Comparing Approaches to (Sub-)Register Variation

pp 75-100

4 - Comparing Baselines for Corpus Analysis

pp 101-126

5 - Comparing Study Designs and Down-Sampling Strategies in Corpus Analysis

pp 127-160

Part III - Perspectives on Multifactorial Methods

pp 161-288

6 - Comparing Generalised Linear Mixed-Effects Models, Generalised Linear Mixed-Effects Model Trees and Random Forests

pp 163-193

7 - Comparing Logistic Regression, Multinomial Regression, Classification Trees and Random Forests Applied to Ternary Variables

pp 194-223

8 - Comparing Bayesian and Frequentist Models of Language Variation

pp 224-258

Appendix 8.1 - Table of Coefficients for the ML Model Based on the Large Sample, and Some Other Details

pp 250-250

Appendix 8.2 - Table of Coefficients for the ML Model Based on the Large Sample, without the Helper (Parsimonious Model), and Some Other Details

pp 251-251

Appendix 8.3 - Bayesian Model Based on the Large Sample with Weakly Informative Cauchy Priors

pp 252-252

Appendix 8.4 - An ML Model Based on the Small Sample

pp 252-253

Appendix 8.5 - A Bayesian Model with Informative Priors Based on the Small Sample

pp 254-254

Appendix 8.6 - Different Priors and Sensitivity Analysis

pp 255-256

Appendix 8.7 - Diagnostics of Markov Chains

pp 257-258

9 - Comparing Methods for the Evaluation of Cluster Structures in Multidimensional Analyses

pp 259-288

Part IV - Applications of Classification-Based Approaches

pp 289-352

10 - Comparing Corpus-Driven and Corpus-Based Approaches to Diachronic Variation

pp 291-322