Doubly Classified Model with R (PDF)

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.