institute for social research

York University  

Over 40 years of excellence in conducting applied and academic social research
York University
4700 Keele Street
Toronto, ON Canada
M3J 1P3

Telephone: 416-736-5061
Toll-free: 1-888-847-0148
Fax: 416-736-5749
E-mail: isrnews@yorku.ca

Fall 2013 Short Courses

Courses
Longitudinal and Hierarchical Data Analysis
with Mixed Models in R
Advanced Research Design Seminar
An Applied Introduction to SPSS
An Introduction to SAS for Windows

SEM: A Second Course in Structural Equation Modeling

Pre-registration and payment of fees is required for all Short Courses.

Please follow these links for details on:

Course Fees
Registration
Certificate of Completion
Statistical Consulting Service

[Click here for Previous Courses]

Longitudinal and Hierarchical Data Analysis with Mixed Models in R
Instructor:
Professor Georges Monette
Dates:
Thursdays – Sep. 26, Oct. 3, 10, 17 and 24, 2013
Time:
7-10pm
Location:

Room 1004,
Technology Enhanced Learning (TEL) Building

Enrolment Limit:
30

Mixed models provide a flexible approach for the analysis of data in which each subject is observed more than once, or in which subjects are clustered in groups like classes. Mixed models are easily extended to allow non-linear models and response variables that are not normally distributed.

This course emphasizes the visualization of the basic concepts in longitudinal and hierarchical data analysis to help with an understanding of the strengths and limitations of these methods. Topics include: mixed models; clustered data; longitudinal data; extensions of mixed models; the structure of the linear mixed model: fixed effects, random effects, variance and covariance components; how mixed models are used to fit longitudinal data; contextual versus compositional effects, splines, and model building and diagnostics.

This short course assumes familiarity with linear regression as presented, for example, in John Fox, Applied Regression Analysis and Generalized Linear Models, Second Edition (Sage, 2008). Familiarity with the basics of R will also be an asset and participants are encouraged to install R and work through introductory tutorials to prepare for the course. Extensive examples will be given in the R programming environment.

For further information and class notes, please see:
http://scs.math.yorku.ca/index.php/Mixed_Models_with_R

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.

Advanced Research Design Seminar
Instructor:
Professor Bryn Greer-Wootten
Dates:
Tuesdays - Oct. 1, 15, 29 and Nov. 12, 2013
Time:
6-9pm
Location:

Room 5082
Technology Enhanced Learning (TEL) Building

Enrolment Limit:
10

Research design in the social, environmental and behavioural sciences today must consider the choices to be made between quantitative, qualitative and mixed (i.e., both quantitative and qualitative) methods approaches. This short course is designed as a seminar to examine such choices. An introductory presentation distinguishes between these approaches from philosophical perspectives. Subsequent sessions discuss (i) the primary issues, based on assigned readings, (ii) critical reviews of participant-chosen research articles, and (iii) group critique of individual research proposals. Sufficient time between meetings is allowed for the work required for these activities.

Enrolment is limited to 10 in order to maximize the seminar setting. This Short Course is open to everyone, but the participant likely to gain most from the experience is a PhD candidate post-comprehensives or a junior faculty person. It may be necessary to select participants based on their applications: please be sure to enter your reasons for applying for this Short Course in the online Registration Form in the box marked "Additional Information". Applicants will be notified of acceptance one week prior to the first seminar meeting, i.e., by September 24, 2013.

An Applied Introduction to SPSS
Instructor:
Carrie Smith, MA
Dates:
Wednesdays - Oct. 2, 9, 16 and 23, 2013
Time:
1-4:30pm
Location:

Steacie Instructional Lab, Room 021
Steacie Science Library

Enrolment Limit:
35

This course aims to acquaint participants with IBM SPSS Statistics, a popular and respected program for analyzing data that is used across a range of disciplines. The curriculum has been recently revised to not only introduce the basic functions and features of the software (including data entry and manipulation), but also to demonstrate how to conduct a range of statistical analyses. Hands-on exercises will supplement the lecture material.

The curriculum for this course is designed to be an applied introduction to a statistical program; as such, familiarity with basic statistical procedures (e.g., t-tests, ANOVA, regression) is assumed. Further, participants are encouraged to bring a USB flash drive to store their work.

Please note that the Steacie Instructional Lab
[Steacie 021] is accessed by entering Steacie Library and then proceeding to the basement of that Library.

Because these materials are presented sequentially and build upon the basics presented at the beginning of each day, course participants need to arrive on time and attend the entire sessions.

Please note that food and drink are not allowed in Steacie Library and the Steacie Instructional Lab. The only exceptions are capped bottles of water (not juice/pop) and spill proof mugs (not cups of coffee). Washrooms are available nearby outside the library.

Click here to download the SPSS course data in a zip file


Sorry, course full
An Introduction to SAS for Windows
Instructor:
Ryan Barnhart, MA
Dates:
Fridays - Oct. 4, 11, 18 and 25, 2013
Time:
9am-12:30pm
Location:

Steacie Instructional Lab, Room 021
Steacie Science Library

Enrolment Limit:
35

This short course provides an introduction to the Statistical Analysis System (SAS) syntax commands and procedures. We will cover the basics of:

  • reading, transforming, sorting, merging and saving data files in some common formats;
  • selecting cases, and modifying and computing variables;
  • performing some basic statistical procedures and tests such as descriptive statistics, correlations, contingency tables, Chi-square tests, t-tests, ANOVA and linear regression;
  • creating bar charts and scatter plots;
  • composing simple macros for tailored procedures; and
  • saving output results and work in some common formats.

This course is designed for participants with some introductory level statistical knowledge, but no previous experience in using SAS. Please note that while this course will focus on the implementation of introductory statistics in SAS, it is not intended as a review of basic statistics. This short course will get you well underway in using SAS.

Please note that the Steacie Instructional Lab
[Steacie 021] is accessed by entering Steacie Library and then proceeding to the basement of that Library.

Because these materials are presented sequentially and build upon the basics presented at the beginning of each day, course participants need to arrive on time and attend the entire sessions.

Please note that food and drink are not allowed in Steacie Library and the Steacie Instructional Lab. The only exceptions are capped bottles of water (not juice/pop) and spill proof mugs (not cups of coffee). Washrooms are available nearby outside the library.

Click here for the SAS course materials

SEM:
A Second Course in Structural Equation Modeling
Instructors: Professor Robert Cribbie
Dates: Thursdays - Nov. 7, 14 and 21, 2013
Time: 9-11:30am
Locations:

Room 159 (Hebb Lab),
Behavioural Sciences Building (BSB)

Enrolment Limit: 20

This course will expand on topics in structural equation modeling (SEM) that are often not fully developed in introductory SEM courses. Topics will include missing data strategies, mediation and moderation, latent class analysis, growth curve modeling, and more. The course will involve both lectures and hands-on exercises (using the AMOS software package).

Because these materials are presented sequentially and build upon the basics presented at the beginning of each class, course participants need to arrive on time and attend the entire session.

Course Fees (including HST)

York University students: $45.20 per course

York University faculty and staff: $90.40 per course

Other post-secondary full-time students: $90.40 per course

External participants: $397.76 per course

Course fees must be paid at the time of registration.

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 9:00am to 12:00pm 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 9:00am to 12:00pm 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.

Professor Robert Cribbie is a Professor in the Department of Psychology at York University and the Joint Coordinator with Professor David Flora of the Institute for Social Research’s Statistical Consulting Service. He received his PhD in Quantitative Psychology from the University of Manitoba. His research interests include multiple comparison procedures, robust ANOVA strategies, and equivalence testing.

Professor Bryn Greer-Wootten is Professor Emeritus in Environmental Studies and Professor Emeritus of Geography at York University. In 2002 he joined the staff in the Statistical Consulting Service, where he is currently an Associate Coordinator, and in 2004 was appointed an Associate Director of ISR. He has taught and carried out quantitative and qualitative research, with a particular interest in survey research, especially for environmental and social policy.

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.

Carrie Smith is a PhD Candidate in Psychology at York University specializing in Quantitative Methods. She received her MA in Psychology at York, and BASc in Engineering at the University of Toronto. Her research interests include data visualization and developing robust methods of statistical analysis appropriate for behavioural science data. She has been using R for statistical computing in her research and consulting for several years.

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 drawn from York University's Departments of Sociology, Psychology, Geography, and Mathematics and Statistics, in conjunction with full-time professional staff at ISR. The faculty and staff have extensive experience with all 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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