Quantitative Data Analysis for Language Assessment Volume II: Advanced Methods demonstrates advanced quantitative techniques for language assessment. The volume takes an interdisciplinary approach and taps into expertise from language assessment, data mining, and psychometrics. The techniques covered include Structural Equation Modeling, Data Mining, Multidimensional Psychometrics and Multilevel Data Analysis.Volume II is distinct among available books in language assessment, as it engages the readers in both theory and application of the methods and introduces relevant techniques for theory construction and validation. This book is highly recommended to graduate students and researchers who are searching for innovative and rigorous approaches and methods to achieve excellence in their dissertations and research. It is also a valuable source for academics who teach quantitative approaches in language assessment and data analysis courses.

Quantitative Data Analysis for Language Assessment Volume I: Fundamental Techniques is a resource book that presents the most fundamental techniques of quantitative data analysis in the field of language assessment. Each chapter provides an accessible explanation of the selected technique, a review of language assessment studies that have used the technique, and finally, an example of an authentic study that uses the technique. Readers also get a taste of how to apply each technique through the help of supplementary online resources that include sample data sets and guided instructions. Language assessment students, test designers, and researchers should find this a unique reference as it consolidates theory and application of quantitative data analysis in language assessment.

Quantitative Data Analysis for Language Assessment Volume I: Fundamental Techniques is a resource book that presents the most fundamental techniques of quantitative data analysis in the field of language assessment. Each chapter provides an accessible explanation of the selected technique, a review of language assessment studies that have used the technique, and finally, an example of an authentic study that uses the technique. Readers also get a taste of how to apply each technique through the help of supplementary online resources that include sample data sets and guided instructions. Language assessment students, test designers, and researchers should find this a unique reference as it consolidates theory and application of quantitative data analysis in language assessment.

Quantitative Data Analysis for Language Assessment Volume II: Advanced Methods demonstrates advanced quantitative techniques for language assessment. The volume takes an interdisciplinary approach and taps into expertise from language assessment, data mining, and psychometrics. The techniques covered include Structural Equation Modeling, Data Mining, Multidimensional Psychometrics and Multilevel Data Analysis.Volume II is distinct among available books in language assessment, as it engages the readers in both theory and application of the methods and introduces relevant techniques for theory construction and validation. This book is highly recommended to graduate students and researchers who are searching for innovative and rigorous approaches and methods to achieve excellence in their dissertations and research. It is also a valuable source for academics who teach quantitative approaches in language assessment and data analysis courses.

Over the years, various approaches to validation have emerged in psychological and educational assessment research, which can be classified into traditional approaches and modern approaches. Traditional approaches view validity as a multicomponential concept including, for example, content, construct, and predictive validity, while modern approaches conceptualize it as a unitary concept evaluated through argumentation. Drawing on the modern approach, this book builds a validity argument for an International English Language Testing System (IELTS) listening test sample. The book provides some insights into the listening sub-skills that the test engages, the psychometric dimensionality of the test, variables that predict item difficulty parameters, bias across age, nationality, test experience, and gender, as well as predictive-referenced evidence of validity. A variety of techniques including the Rasch model and structural equation modelling are used to answer the research questions and to build a validity argument framework; this argument organizes the thematically related findings into a coherent treatment of the validity of the listening test. The book presents the first treatment of validity argument and related analytical tools in one volume and maps the psychometric/statistical analysis tools onto the validity argument framework. It also provides an extensive literature review of listening comprehension, validation, and psychometric modeling and proposes both methods for developing and validating self-assessment instruments and novel approaches to improving the quality of language assessments.