Longitudinal Data Analysis

Longitudinal Data Analysis in

Business- and Bio-Statistics

One-Day Workshop

SAS Canada, 280 King Street East, Fifth Floor, Toronto, Ontario, M5A 1K7

May 10, 2007, 9:00am – 4:30pm

| Abstracts

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| Course Materials

| Visitor Information

| Organizing Committee

“The dissemination of the MIXED procedure in SAS and related software has provided a whole class of linear mixed-effects models, some … with a long history, for routine use. Experience shows that both the ideas behind the techniques and their software implementation are not at all straightforward and users from various applied backgrounds often encounter difficulties in using the methodology effectively.”

    This is the opening paragraph in the preface to Verbeke and Molenburghs’ Linear Mixed Models for Longitudinal Data (New York: Springer, 2000), and, even after seven years, still describes a situation in which many applied statisticians find themselves. In fact, with the advent of generalized linear mixed models and SAS’ GLIMMIX procedure, the complexity of analyses facing statisticians has only increased.

    Business statisticians often ignore correlations between transactions within a single customer, whether that customer is an individual or a business. The tendency is to summarize transactional data to a single row for analysis, with, perhaps, a severe loss of information. Biostatisticians, as a whole, have used longitudinal data methods for many years. However, new methods continue to be developed and biostatisticians must keep pace.

    This one-day workshop is designed to enhance participants’ knowledge in the application of longitudinal data analysis methods, specifically the linear and generalized linear mixed models. Lecture style presentations are followed by hands-on computer workshops where discussed methods are applied to real-world data.

Intended for applied statisticians in business and biostatistics.

Registration fee is $75 per person, lunch included.


SAS Institute (Canada), Inc.		The Southern Ontario Regional Association of the Statistical Society of Canada (SORA)		Department of Public Health Sciences, University of Toronto	The Applied Biostatistics Association (TABA)