Title: Handbook of quantitative methods for educational research /
Authors: Teo, Timothy,
Year: 2013
Subjects: Education Research Methodology; Quantitative research.
Abstract: As part of their research activities, researchers in all areas of education develop measuring instruments, design and conduct experiments and surveys, and analyze data resulting from these activities. Educational research has a strong tradition of employing state-of-the-art statistical and psychometric (psychological measurement) techniques. Commonly referred to as quantitative methods, these techniques cover a range of statistical tests and tools. Quantitative research is essentially about collecting numerical data to explain a particular phenomenon of interest. Over the years, many methods and models have been developed to address the increasingly complex issues that educational researchers seek to address. This handbook serves to act as a reference for educational researchers and practitioners who desire to acquire knowledge and skills in quantitative methods for data analysis or to obtain deeper insights from published works. Written by experienced researchers and educators, each chapter in this handbook covers a methodological topic with attention paid to the theory, procedures, and the challenges on the use of that particular methodology. It is hoped that readers will come away from each chapter with a greater understanding of the methodology being addressed as well as an understanding of the directions for future developments within that methodological area.
Contents: Section 1: Measurement Theory -- 1. Psychometrics / Mark Wilson & Perman Gochyyev -- 2. Classical test theory / Ze Wang & Steven J. Osterline -- 3. Item response theory / Xitao Fan & Shaojing Sun -- Section 2: Methods of analysis -- 4. Multiple regression / Ken Kelley & Jocelyn Holden -- 5. Cluster analysis / Christine DiStefano & Diana Mindrila -- 6. Multivariate analysis of variance: with discriminant function analysis follow-up / Lisa L. Harlow & Sunny R. Duerr -- 7. LoGistic regression / Brian F. French, Jason C. Immekus & Hsiao-Ju Yen -- 8. Exploratory factor analysis / W. Holmes Finch -- 9. A brief introduction to hierarchical linear modeling / Jason W. Osborne & Shevaun D. Neupert -- 10. Longitudinal data analysis / D. Betsy McCoach, John P. Madura, Karen E. Rambo-Hernandez, Ann A. O'Connell & Megan E. Welsh -- 11. Meta-analysis / Spyros Konstantopoulos -- 12. Agent based modelling / Mauricio Salgado & Nigel Gilbert -- 13. Mediation, moderation & interaction: definitions, discrimination & (some) means of testing / James Hall & Pamela Sammons -- Section 3: Structural equation models -- 14. Introduction to confirmatory factor analysis and structural equation modeling / Matthew W. Gallagher & Timothy A. Brown -- 15. Testing measurement and structural invariance: implications for practice / Daniel A. Sass & Thomas A. Schmitt -- 16. Mixture models in education / George A. Marcoulides & Ronald H. Heck -- 17. Selecting SEM computer programs: considerations and comparisons / Barbara Byrne