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Winter 2007 Short Courses
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The 2007 Winter Courses have concluded.
Pre-registration and payment of fees is required for all Short Courses. |
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Instructor:
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Professor Georges Monette |
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Dates:
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February 1, 8, 22, March 1 and 8, 2007 (Thursdays) |
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Time:
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6:00 pm - 9:00 pm |
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Location:
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Room 0011 Technology Enhanced Learning Bldg. |
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Enrolment Limit:
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25 |
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 will emphasize the visualization of the basic concepts in longitudinal and hierarchical data analysis to help participants develop a strong understanding of the strengths and limitations of these methods. The proposed list of topics includes the following: 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. Statistical control with observational data. Borrowing strength, shrinkage and bias in random effects models. Contextual versus compositional effects. Model building and diagnostics. Consequences of measurement error and approaches to adjustment. modeling correlation. Missing data patterns. modeling panel attrition. Logistic regression for binary responses. Non-linear models for binary and categorical responses.
This Short Course assumes familiarity with linear regression methods as presented, for example, in John Fox, Applied Regression Analysis, Linear Models, and Related Methods, Sage 1997.
An Introduction to SAS for Windows
Nikolai Slobodianik Feb. 7, 21, 28, Mar. 7, 2007
(Wednesdays)10:30 am - 1:30 pm Steacie Instructional Lab,
Room 021, Steacie Science Library35 This short course provides a basic introduction to the Statistical Analysis System (SAS). Sessions One and Two provide: an overview of SAS and its underlying logic; an explanation of the use of the Display Manager System to run a SAS job; an introduction to the SAS Data step for reading, importing, transforming and storing numeric and character data; and, a demonstration of how output can be changed with different options. In addition, some basic procedures in SAS will be introduced.
Sessions Three and Four will concentrate on SAS programming techniques to modify data, create charts and plots and transform temporary datasets to permanent datasets. A demonstration of how to use SAS/INSIGHT and SAS/ANALYST will be presented, as well as a basic description of the general linear model. The course is designed for participants with some introductory level statistical knowledge, but no previous experience in using SAS.
Introduction to SPSS for Windows
Lisa Fiksenbaum, MA Feb. 8, 22, Mar. 1, 8, 2007
(Thursdays)9:00 am - 12:30 pm Steacie Instructional Lab,
Room 021, Steacie Science Library35 This course presents the basics of the Statistical Package for the Social Sciences (SPSS). Session One will introduce the computing concepts of SPSS, the different facilities for reading data into an SPSS spreadsheet, and saving SPSS data files for future use. At the end of the first session, participants should be able to run simple programs, including some statistical procedures.
Sessions Two and Three will cover basic data modifications, transformations and other functions, including the uses of SPSS system files. More statistical procedures will also be introduced, with an emphasis on the use of graphical methods for examining univariate and bivariate relationships. Session Four will cover Analysis of Variance and Least Squares Regression. As with previous sessions, graphical techniques will be demonstrated. Participants will benefit if they have a basic level of statistical knowledge up to general linear models, but the course is designed as an introduction to data analysis using the SPSS program and not as a statistics course.
Categorical Data Analysis with Graphics
Professor Michael Friendly February 28, March 7 and 14, 2007
(Wednesdays)1:30 - 4:30 p.m. Room 291
Behavioural Sciences Bldg.30 Statistical methods for categorical data, such as log-linear models and logistic regression, represent discrete analogs of the analysis of variance and regression methods for continuous response variables.
While graphical display techniques are common adjuncts to analysis of variance and regression, methods for plotting contingency table data are not as widely used. Moreover, while statistical methods can be used to determine which variables are related, the numerical summaries and parameter estimates do not provide easy ways to show how those variables are related.
This workshop provides a brief introduction to statistical methods for analysing discrete data and frequency data, together with some of the graphical methods which are useful for understanding the pattern of association among categorical variables. These methods can be helpful for both data exploration and for communicating results to others. Some of the methods described include:
methods for discrete frequency distributions,
association plots for two-way tables,
mosaic displays,
effects plots for log-linear models and logistic regression,
correspondence analysis, and
models for repeated measures.These graphical techniques are illustrated with real data in the form of two-way and multi-way frequency tables. Course notes will provide many detailed examples. The various techniques are all described and illustrated in Professor Friendly's book, Visualizing Categorical Data, Cary, NC: SAS Press, 2000.
- For York students, staff, and faculty, the fee is $40 per course.
- Full-time students at other post-secondary institutions may enroll for a fee of $60 per course.
- For external participants, the fees per course are:
- Longitudinal and Hierarchical Data Analysis
with Mixed Models.................................................. $240 - Introduction to SAS for Windows.............................$240
- Introduction to SPSS for Windows...........................$240
- Categorical Data Analysis with Graphics................$180
- Longitudinal and Hierarchical Data Analysis
- All participants, Certificate of Completion ......................$5.00 each
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:
Anita Valencia
Room 5075
Technology Enhanced Learning (TEL) Building
- To register by mail, print a blank registration form,
complete, and send to:
Anita Valencia
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
- For further information, please telephone 416-736-5061, weekdays, from 9:00am to 12:00pm or 2:00pm to 4:00pm
- Directions to York University (Keele Campus), information on parking and building locations click here.
- Available on request, full attendance is required.
- A $5.00 administrative fee applies, for each certificate requested.
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 LISREL 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 staff also assist in teaching these topics by giving presentations in regular university classes.
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. Appointments can be made at http://www.isr.yorku.ca/scs with the on-line Appointment Scheduler.
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