My favourite sarimanok (mythical rooster).

Alexander R. de Leon


Contact information

Web presence

Phone number

Office: +1 (403) 220-6782


Office: MS588


Educational Background

PhD Statistics , University of Alberta, 2002


Originally from the Philippines, Alexander R. de Leon received his PhD in Statistics from the University of Alberta. He is currently an associate professor in the Department of Mathemattics and Statistics at the University of Calgary, where he enjoys teaching a wide variety of courses. He is interested in all aspects of statistics and likes to think about them while binge-streaming his favourite shows.  He was an associate editor of the Journal of Statistical Computation & Simulation (2013-2021) and Research Methods in Medicine & Health Sciences (since 2020).  His research is supported by the Natural Sciences & Engineering Research Council (NSERC) of Canada. I served as Co-Chair (with Dr. Karen Kopchuk) of Local Arrangements Committee for 2019 Statistical Society of Canada Anual Meeting at the Universit of Calgary.  I was also the WNAR-IBS Representative on the Program Committee for 2015 Joint Statistical Meetings in Seattle, WA.


Areas of Research

Assessment of diagnostic tests, Copula models, Estimating functions and estimating equations, Joint models, Methods for correlated data, Mixed effects models, Models for mixed discrete and continuous outcomes, Pseudo- and composite likelihood methods, Statistical problems in medicine

Participation in university strategic initiatives


Course number Course title Semester
STAT 421 Mathematical Statistics Fall 2023
DATA SCIENCE 606 Statistical Methods in Data Science Winter 2024
STAT 517 Practice of Statistics Winter 2024


  • GREAT Supervisor Award, Faculty of Graduate Studies, University of Calgary. 2013
  • 2003 Joint Statistical Meetings Best Student Paper, Health Policy Statistics Section, American Statistical Association. 2003
  • Pundit RD Sharma Memorial Graduate Award in Mathematical and Statistical Sciences, Department of Mathematical and Statistical Sciences, University of Alberta. 1999
  • TUBITAK Visiting Scientist, Middle East Technical University, Government of Turkey. 2013
  • Visiting Professor, School of Statistics, University of the Philippines-Diliman. 2017


More Information

  1. Jia Li, Correlated Data Analysis via EM Algorithm and Its Variants: Applications to Data on Physical Activity and Maternal Health (Expected completion: August 2024, Co-supervisor: Dr. Haocheng Li, Roche).
  2. Fahmida Yeasmin (Expected completion: Fall 2024, Co-supervisor: Dr. Hua Shen, University of Calgary).
  3. Joyce Raymund B. Punzalan, Joint Estimation of Diagnostic Accuracy Measures of Correlated Diagnostic Tests for Paired Organs in the Absence of a Gold Standard, School of Statistics, University of the Philippines-Diliman.
  1. Mingchen Ren, 2022, Causal Inference with Mismeasured Confounders or Mediators.   (Co-supervisor:  Dr. Ying Yan, Sun Yat-sen University)
  2. Niroshan Withanage, 2013, Methods and Applications in the Analysis of  Correlated Non-Gaussian Data. (Senior Lecturer, Department of Statistics, University of Jayewardenepura, Colombo, Sri Lanka)
  3. Beilei Wu, 2013, Contributions to Copula Modelling of Mixed Discrete-Continuous Outcomes. (Principal Biostatistician, PPD) 
  1. Michael John Ilagan, 2020, A Goodness-of-Fit Test for the Bivariate Necessary-But-Not-Sufficient Relationship. (Co-Supervisor: Dr. Karen Kopciuk, Tom Baker Cancer Centre)
  2. Austin Mu Qing Ren, 2020, Analysis of Metabolomics Data via Mixed Models. (Co-Supervisor: Dr. Karen Kopciuk, Tom Baker Cancer Centre)
  3. Ajmery Jaman, 2019, Joint Modeling of Clustered Binary Data with Crossed Random Effects via the Gaussian Copula Mixed Model.
  4. Katherine L. Burak, 2019, Cluster Analysis of Correlated Non-Gaussian Continuous Data via Finite Mixtures of Gaussian Copula Distributions.
  5. Saifa Raz, 2016, COM-Poisson Clustering of Correlated Bivariate Over- and Under-Dispersed Counts.
  6. Mingchen Ren, 2016, Likelihood Analysis of Gaussian Copula Distributions for Mixed Data via a Parameter-Expanded Monte Carlo EM (PX-MCEM) Algorithm. (Co-supervisor:  Dr. Ying Yan, Sun Yat-sen University)
  7. Mili Roy, 2016, Conditional Dependence in Joint Modelling of Longitudinal Non-Gaussian Outcomes.
  8. Ji, Ruan, 2015, Cluster Analysis of Gene Expression Profiles via Flexible Count Models for RNA-seq Data.
  9. Fahmida Yeasmin, 2015, Analysis of Serially Dependent Multivariate Longitudinal Non-Gaussian Continuous Data.
  10. Yamuni Singappuli Perera, 2013, Binocular Sensitivity and Specificity of Screening Tests in Prospective Studies of Paired Organs.
  11. Yifan Zhu, 2010, Evaluation of Binocular Screening Tests: A Copula Approach via "Continued" Binary Outcomes.
  12. Yongtao Zhu, 2006, ANOVA Extensions for Mixed Discrete and Continuous Data.
  13.  Meiji Guo, 2005, A Likelihood-Based Approach to Estimating Sensitivity and Specificity with Binocular Diagnostic Data—Application in Ophthalmology.