Statistical Consulting Service (SCS) Consultants
Make an appointment with a Statistical Consultant.
Mahdis Azadbakhsh received her Master’s degree in Theoretical Statistics from York University and is currently a PhD student in Statistics at York. Her research interests include shape-constraint density estimation, composite likelihood estimation and model selection. She is now a Teaching Assistant in the Department of Mathematics and Statistics and can help in data analysis using R and SAS.
Ryan Barnhart is a PhD candidate in Psychology at York University with specialization in Quantitative Methods, under Dr. Michael Friendly. Ryan’s research interests and statistical work has focused upon longitudinal data analysis using multilevel modeling and generalized linear multilevel modeling. This work has helped him to develop a multiplatform approach to using statistical software, including SAS, STATA, R and SPSS.
Phil Chalmers is a PhD student at York University studying Quantitative Methods in Psychology, specifically psychometrics and latent variable modeling techniques, such as item response theory and structural equation modeling. Phil is currently a TA comfortable with using Mplus, R, and SPSS programming and analysis.
Alyssa Counsell is a doctoral candidate in the Quantitative Methods program in Psychology. Her research interests include equivalence testing, robust statistics, measurement invariance, structural equation modeling, and pedagogical methods for improving statistical knowledge in applied psychological research. She is currently an SCS TA with proficiency in both SPSS and R.
Professor Robert Cribbie
Robert Cribbie is a Professor in the Department of Psychology at York University. He received his PhD in Quantitative Psychology from the University of Manitoba. His research interests include multiple comparison procedures, robust ANOVA strategies, and structural equation modeling.
On sabbatical leave 2014-2015.
Professor David Flora
David Flora is an Associate Professor in the Department of Psychology at York University and Joint Coordinator of the Statistical Consulting Service (2014-2015). He received his PhD in Quantitative Psychology from the University of North Carolina at Chapel Hill. His research interests include longitudinal data analysis, psychometric analysis, factor analysis, and structural equation modeling.
Professor John Fox
John Fox is Senator William McMaster Professor of Social Statistics in the Sociology Department at McMaster University and an Associate Coordinator of the Statistical Consulting Service at York. He teaches at the Inter-University Consortium for Political and Social Research in Ann Arbor and is the author of Applied Regression and Generalized Linear Models, Second Edition (Sage, 2008) and An R and S-PLUS Companion to Applied Regression(Sage, 2002), among other works. Professor Fox holds a PhD from the University of Michigan.
Professor Michael Friendly
Michael Friendly received his doctorate in Psychology from Princeton University, specializing in Psychometrics and Cognitive Psychology. He is a Professor of Psychology at York and Joint Coordinator of the Statistical Consulting Service (2014-2015). In addition to his research interests in psychology, Professor Friendly has broad experience in data analysis, statistics and computer applications. He is the author of SAS for Statistical Graphics, 1st Edition and Visualizing Categorical Data, both published by SAS Institute, and an Associate Editor of the Journal of Computational and Graphical Statistics and Statistical Science. His recent work includes the further development of graphical methods for categorical data and multivariate data analysis.
Professor Bryn Greer-Wootten
Bryn Greer-Wootten is Professor Emeritus in Environmental Studies and Geography, and an Associate Coordinator with the Statistical Consulting Service. His research interests are in the area of environmental policy and planning. In particular, they include community responses to high-level nuclear waste facility siting, local conflicts in provincial waste management policies, scientific and elite discourse in global climate change policy formulation, and cross-cultural representations of folk narratives on the environment.
Joo Ann Lee
Joo Ann Lee is a MA2 student in the Department of Psychology at York University studying quantitative methods under Dr. David Flora. Joo Ann is currently a TA comfortable with using SAS, SPSS, Minitab and R for data analysis and is experienced with univariate analysis. Joo Ann’s current research is in the area of meta-analysis and interrupted time series analysis.
Hugh McCague is Data Analyst and Statistical Consultant at ISR. He has worked as a statistician in both private and public sectors. He completed a PhD in Environmental Studies and an MA in Statistics at York University. His research and publications have concentrated on applications of mathematics and statistics in architectural history and archaeology. He has taught research and computer skills to undergraduate students in Arts at York University, in addition to regular consulting.
Professor Georges Monette
Georges Monette is an Associate Professor of Mathematics and Statistics at York and an Associate Coordinator with the Statistical Consulting Service. Most of his research has been in the mathematical foundations of statistical inference. His recent interests are the geometric visualization of statistical concepts and the modeling and analysis of longitudinal data. He has worked in a number of applied areas, including pay equity and the statistical analysis of salary structures. He received his PhD in Statistics from the University of Toronto.
Professor Peggy Ng
Dr. Peggy Ng received her PhD in Preventive Medicine and Biostatistics from University of Toronto. She is a Professor in Management Sciences and Applied Statistics. Her research focus has been in biostatistics, experimental design, psychometrics and their applications in Health Sciences. Her recent research interests include panel data analysis in organizational data and knowledge creation, and the use of a soft approach for hard optimization models. Peggy is the past president of the Southern Ontario Regional Association of the Statistical Society of Canada.
David Northrup is Director of Survey Research at ISR and is responsible for the design and management of major surveys at the Institute. He has over 25 years of experience in questionnaire design and data collection. His research interests include survey methodology, election studies, public policy, and how Canadians explore the past in everyday life. Mr. Northrup holds an MA and he teaches survey research methods at York University.
Mirka Ondrack received her Master’s degree in Physics from Masaryk University in the Czech Republic and spent two years studying industrial engineering at the University of Toronto. She has held the position of Programmer/Analyst at ISR since 1971. Ms. Ondrack is currently a consultant with the Statistical Consulting Service and also does custom programming and data analysis. She has been teaching courses on SAS and SPSS since 1981. Mirka consults on statistical computing using SPSS and SAS; data screening and statistical graphics; regression, ANOVA and other linear models; factor analysis.
Stella Park is a Project Manager, and teaches an NVivo for Windows course at ISR. Stella provides NVivo consultation to graduate students, faculty, and non-profit sector professionals. She has over 10 years of experience in conducting both quantitative and qualitative research projects at the local, provincial, and international levels on a diverse range of topics, including health, education, employment, and non-profit sector. At ISR, she uses NVivo software to analyze several qualitative research projects, including the YouthREX project and the Experiential Education Project.
Professor Jolynn Pek
Jolynn Pek is an Assistant Professor in the Department of Psychology at York University and an Associate Coordinator with the Statistical Consulting Service. She received her PhD in Quantitative Psychology from the University of North Carolina at Chapel Hill. Her research interests involve quantifying different aspects of uncertainty in results obtained from fitting latent variable models (e.g., factor analysis models, structural equation models, structural equation mixture models, multilevel models, and latent growth curve models) to data.
Professor Michael Rotondi
Michael Rotondi is an Assistant Professor of Biostatistics in the School of Kinesiology and Health Sciences. He received his PhD in Biostatistics from the University of Western Ontario and completed a post-doctoral fellowship at the Samuel Lunenfeld Research Institute in statistical genetics. His research interests include the design and analysis of cluster randomized trials, studies of interobserver agreement and statistical genetics.
Bin Sun is a PhD student in Statistics in the Department of Mathematics and Statistics at York University. She was a part-time biostatistician at Princess Margaret Hospital for two years. Her primary research interest now is Semi-Parametric modeling with missingness. She has experience in longitudinal data analysis, mixed modeling, survival analysis and genetic statisics with R and SAS.
Xiaoying Sun completed her MA degree in Statistics at York University and is currently pursuing her PhD degree. Her doctoral research area is model selection, change point detection and spatio-temporal modeling. Xiaoying is currently a TA with SCS and is able to help with data analysis such as ANOVA, MANOVA, (generalized) linear regression, mixed models using R.
Amanda Tian is a PhD student in the Department of Mathematics and Statistics at York University. Her doctoral research area is discrete log-concave density estimators in multiple dimension space. She is currently an SCS TA, and would like to help in the following areas: hierarchical and longitudinal mixed models, generalized linear mixed models, R and SPSS.
Yawen Xu is a PhD student in the Department of Mathematics and Statistics at York University. Prior to this, Yawen graduated from the Financial Engineering Program in the Schulich School of Business. Her main research interests are regression models, generalized linear models, longitudinal data analysis and numerical methods for Finance. Yawen is proficient in Splus/R, SAS and Maple.