April 1, 2015

Winter 2015 Short Courses will resume
and be completed in the week of April 6, 2015.

An Introduction to Meta-analysis and Systematic Reviews
Instructor:	Professor Michael Rotondi
Dates:	Fridays - Jan. 30, Feb. 6 and 13, 2015
Time:	9:30am - 12:30pm
Location:	Room 159 (Hebb Lab), Behavioural Sciences Building (BSB)
Enrolment Limit:	20
This course provides an introduction to the role of meta-analysis and systematic reviews in evidence-based medicine. Statistical and practical issues relating to the design and interpretation of meta-analyses and systematic reviews are emphasized. Selected topics include: What is a meta-analysis? Defining the research question Searching for and selecting studies for inclusion Statistical methods and interpretations Fixed and random effects models Performing meta-analyses in R Advanced topics including meta-regression and incorporation of other study designs (prospective cohorts and cluster randomized trials) will also be discussed. This course is designed for participants with introductory knowledge of statistics and statistical computing, but no prior exposure to meta-analysis is expected. Statistical computing is performed in the R environment, thus some prior knowledge of R is an asset. Because this material is presented sequentially and builds upon the basics presented at the beginning of each class, course participants need to arrive on time and attend the entire session.

See the registration form for payment options.

Refunds are available upon three business days' notice prior to the course start date and are subject to an administrative fee.

Please review our policy regarding refunds here.

Registration

You can register for courses by completing the on-line registration form.

To register in person (weekdays, from 10:00am to Noon or
2:00pm to 4:00pm), please see:

Betty Tai
Room 5075
Technology Enhanced Learning (TEL) Building

To register by mail, print a blank registration form, complete,
and send to:

Betty Tai
Institute for Social Research
Room 5075
Technology Enhanced Learning Building
York University
4700 Keele Street
Toronto, ON M3J 1P3
Canada

You may also fax a completed registration form to: 416-736-5749

Certificate of Completion

Available on request, full attendance is required.

A $5.65 administrative fee (including HST) applies,
for each certificate requested.

Additional Information

Additional information regarding registration:
please telephone 416-736-5061, weekdays,
from 10:00am to Noon or 2:00pm to 4:00pm

Directions to York University (Keele Campus), building and parking lot locations click here. For additional information on parking click here.

Instructors

Ryan Barnhart is a PhD candidate in Psychology at York University with specialization in Quantitative Methods. His research interests and statistical work have focused on longitudinal data analysis using multilevel modeling and generalized linear multilevel modeling. This work has helped Mr. Barnhart develop a multi-platform approach to using statistical software, including SAS, STATA, R and SPSS.

Alyssa Counsell is a second year 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.

Hugh McCague is a statistician at the Institute for Social Research and Statistical Consulting Service at York University. His work and research concentrate on applications of statistics in health and environmental studies, including the use of data at the Statistics Canada Research Data Centre at York University.

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.

Michael Rotondi is an Assistant Professor of Biostatistics and Quantitative Methods in the School of Kinesiology and Health Science, and an Associate Coordinator with the Statistical Consulting Service. His research interests span a variety of biostatistical areas, and include the development of statistical methods to estimate power and sample size for meta-analysis and meta-regression models. He has also performed meta-analyses examining the impact of vitamin A supplementation on neonatal mortality, and the role of physical activity in the prevention and treatment of Alzheimer’s disease.

Sara Tumpane is the Analyst at the Statistics Canada Research Data Centre on the York University campus. In addition, she is a Ph.D. Candidate in the Department of Economics at York University, with a focus on quantitative research in health and environmental economics.

Statistical Consulting Service (SCS)

The Institute for Social Research's Statistical Consulting Service provides consultation on a broad range of statistical problems and on the use of computers for statistical analysis. Its services extend beyond the social sciences to other disciplines that make use of statistics. Consultation is available to assist in research design, data collection, data analysis, statistical computing and the presentation of statistical material.

Consultation is provided by a group of faculty and graduate students drawn from York University's Departments of Sociology, Psychology, Geography, Mathematics and Statistics, and the School of Kinesiology and Health Science, in conjunction with full-time professional staff at ISR. The consultants have extensive experience with most forms of statistical analysis. Topics for which assistance is available include regression analysis, multivariate analysis, stochastic processes, probability theory, exploratory data analysis, scaling and cluster analysis, analysis of categorical data, structural equation modeling, survey data and longitudinal data, experimental design, survey sampling, and statistical computing.

Three times a year, the Statistical Consulting Service offers short courses on various aspects of statistics and statistical computing, including regular introductions to the SPSS and SAS statistical packages. Recent course offerings have included regression diagnostics, boot-strapping techniques, an introduction to the AMOS module in SPSS, graphical methods for categorical data, confirmatory factor analysis, model-based approaches to cluster analysis, introduction to the R programming language, and visual methods for statistical data analysis.

The Statistical Consulting Service maintains a regular schedule of office hours during the academic year. The Service primarily serves the York University community; for others, consultation is available on a fee-for-service basis. Please go to the Institute's web site at www.isr.yorku.ca/scs to make appointments online with SCS consultants.

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