Advancing Quantitative Methods in Second Language Research is the first hands-on guide to conducting advanced research methods in the fields of applied linguistics and second language studies. While a number of texts discuss basic quantitative research methodology, none focus exclusively on providing coverage of alternative advanced statistical procedures in second language studies from a practical approach. The text is bookended by discussions of these advanced procedures in the larger context of second language studies, debating their strengths, weaknesses, and potential for further research; the remaining chapters are how-to sections, each chapter following the same organization, on a wide variety of advanced research methods. By offering much-needed coverage on advanced statistical concepts and procedures, with an eye toward real-world implementation,Advancing Quantitative Methods in Second Language Research enhances the methodological repertoire of graduate students and researchers in applied linguistics and second language studies.
For additional content, visit: http://oak.ucc.nau.edu/ldp3/AQMSLR.html
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xi | |
| Acknowledgments |
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xvii | |
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xix | |
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1 | (20) |
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3 | (6) |
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2 Why Bother Learning Advanced Quantitative Methods in L2 Research? |
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9 | (12) |
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PART II Enhancing Existing Quantitative Methods |
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21 | (108) |
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3 Statistical Power, p values, Descriptive Statistics, and Effect Sizes: A "Back-to-Basics" Approach to Advancing Quantitative Methods in L2 Research |
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23 | (23) |
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4 A Practical Guide to Bootstrapping Descriptive Statistics, Correlations, tTests, and ANOVAs |
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46 | (32) |
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5 Presenting Quantitative Data Visually |
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78 | (28) |
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6 Meta--analyzing Second Language Research |
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106 | (23) |
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PART III Advanced and Multivariate Methods |
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129 | (218) |
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131 | (28) |
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8 Mixed Effects Modeling and Longitudinal Data Analysis |
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159 | (23) |
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9 Exploratory Factor Analysis and Principal Components Analysis |
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182 | (31) |
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10 Structural Equation Modeling in L2 Research |
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213 | (30) |
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243 | (32) |
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275 | (30) |
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305 | (24) |
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14 Bayesian Informative Hypothesis Testing |
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329 | (18) |
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| Index |
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347 | |
Luke Plonsky (PhD, Michigan State University) is a faculty member in the Applied Linguistics program at Northern Arizona University. His interests include SLA and research methods, and his publications in these and other areas have appeared in Annual Review of Applied Linguistics, Applied Linguistics, Language Learning, Modern Language Journal, and Studies in Second Language Acquisition, among other major journals and outlets. He is also Associated Editor of Studies in Second Language Acquisition and Managing Editor of Foreign Language Annals.
