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Doubly Classified Model with R

  • Book
  • © 2017

Overview

Authors:
  1. Teck Kiang Tan

    1. Centre for Skills, Performance and Productivity, Institute for Adult Learning, Singapore, Singapore

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  • Assists readers in understanding doubly classified models clearly without referring to numerous technical resources
  • Provides a pioneering, comprehensive and practical approach with doubly classified models
  • Appeals to academic researchers and industry practitioners alike
  • Includes supplementary material: sn.pub/extras

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Table of contents (10 chapters)

  1. Front Matter

    Pages i-xix
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  2. Introduction to R

    • Teck Kiang Tan
    Pages 1-19

  3. Basic Concepts

    • Teck Kiang Tan
    Pages 21-48

  4. Examining Symmetry of Doubly Classified Table

    • Teck Kiang Tan
    Pages 49-61

  5. Symmetry and Asymmetry Models

    • Teck Kiang Tan
    Pages 63-120

  6. Point Symmetry Models

    • Teck Kiang Tan
    Pages 121-156

  7. Non-independence Models

    • Teck Kiang Tan
    Pages 157-191

  8. Asymmetry + Non-Independence Models

    • Teck Kiang Tan
    Pages 193-208

  9. Modeling Strategy

    • Teck Kiang Tan
    Pages 209-223

  10. Creating Doubly Classified Models

    • Teck Kiang Tan
    Pages 225-242

  11. Summary

    • Teck Kiang Tan
    Pages 243-262

  12. Back Matter

    Pages 263-264
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Keywords

About this book

This book provides practical applications of doubly classified models by using R syntax to generate the models. It also presents these models in symbolic tables so as to cater to those who are not mathematically inclined, while numerous examples throughout the book illustrate the concepts and their applications. For those who are not aware of this modeling approach, it serves as a good starting point to acquire a basic understanding of doubly classified models. It is also a valuable resource for academics, postgraduate students, undergraduates, data analysts and researchers who are interested in examining square contingency tables.

Authors and Affiliations

  • Centre for Skills, Performance and Productivity, Institute for Adult Learning, Singapore, Singapore

    Teck Kiang Tan

About the author

Dr Tan works as a research fellow in the Department of Research & Innovation Division, Institute for Adult Learning, Singapore. Teck Kiang completed his Ph.D. at the Nanyang Technological University, Singapore. He received a Bachelor of Accountancy degree, a Master of Science (Statistics) degree at the National University of Singapore and a Master of Accountancy degree at the Auckland University, New Zealand. He is currently a member of psychometric society. His research interests include school compositions and student’s performance, education mismatch, skills utilization, employment vulnerability, and job satisfaction. He shared his research and statistical interests through workshops conducted at conferences, at local universities with faculty members and graduate students, to adult learners, educators and researchers. He also conducted yearly workshop series to adult learners. The workshop topics he had covered include Introduction to R, R Programming, R Graphics, Doubly Classified Models, Multilevel Analysis, Propensity Score Analysis, Decision Trees, Sampling, Inter-rater Reliability and Item Response Theory. 
Teck Kiang has published numerous papers related to school and adult education. His recent useR! Conference 2015 presentation titled “Extending the quasi-symmetry model: Quasi symmetry with n degree” shared a series of newly derived quasi-symmetry models that generalize the quasi-symmetry model to explain the association of generic skills using doubly classified models. A recent written chapter on “The determinants of training participation, A multilevel approach: Evidence from PIAAC” examined the heterogeneity of covariates across 24 countries using multilevel random slope models. 


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