The 2008 SPIDA program covers two important approaches to longitudinal data, multilevel models and structural equation models. Both are widely used to analyze panel surveys, such as Statistics Canada’s longitudinal surveys on health and income.

In longitudinal applications of multilevel models, temporal trajectories, for example a sequence of health measurements over time, are conceptualized as “nested” within each individual survey respondent. Characterizing the sequence with one or more parameters, we can ask whether the trajectory shows improvement, decline or stability, and how this is related to a person’s age, income and other personal characteristics. Not only do multilevel models allow temporal trajectories to be parameterized in a very flexible way, measurements need not be taken at the same time or equally often for each individual, and missing data are easily accommodated. By extending the multilevel model to an additional “level”, we can analyze the effect of families, neighbourhoods, communities and other social groups on the temporal trajectories of individual health, income and other characteristics. This part of SPIDA will be presented by Professor Suzanne Graham of the University of New Hampshire.

The second topic of this year's SPIDA is structural equation models (“SEMs”), the application of which to panel data is often described as the analysis of “growth curves,” even though what is being measured can exhibit any pattern of change over time. SEMs combine ideas of “path analysis,” developed by Sewall Wright in the 1920s to describe causal relationships, and factor analysis, developed in the 1930s to conceptualize “traits”, measured imperfectly by a number of “items”, usually in some kind of questionnaire or test. SEMs are very flexibile in characterizing temporal trajectories and have a unique ability to analyze temporal trajectories in the context of complex causal relations. Also, it is usual for panel surveys to provide measurements at discrete intervals, which produces data appropriate for SEMs. Another advantage of SEMs is that they are now a “mature” technique, in continuous development since the initial work by Jöreskog and Sörbom in the late 1960s. This part of SPIDA will be presented by Professor David Flora of York University.

For the daily computer lab sessions in SPIDA, we will be using the Statistical Analysis System (SAS) because of its flexibility and the availability of support in most social science research environments. For non-SAS users, the first day of SPIDA is a one-day SAS Workshop taught by Mirka Ondrack and Nikolai Slobodianik of the Institute for Social Research’s Statistical Consulting Service.

The 2008 Program, coordinated by Professors Robert Cribbie, Bryn Greer-Wootten and Michael Ornstein, replicates the 2007 Program. Previous SPIDA programs, which began in the summer of 2000, concentrated largely on either multilevel models or SEMs. The 2007 and 2008 Programs bring the two approaches together for longitudinal data.

The proposal for this 2008 - 2010 SSHRC – Statistics Canada grant was developed by a team under the direction of Michael Ornstein, Department of Sociology and Director of the Institute for Social Research, York University. Dr. Ornstein was also the lead organizer of the 2005 - 2007 and 2002 - 2004 CISS Data Training Schools, and an organizing committee member of the two CISS pilot projects in 2000 and 2001.

The organizing committee members:

Michael Baker, Department of Economics, University of Toronto and Academic Director, Toronto Regional Research Data Centre.

Robert Cribbie, Department of Psychology, York University and an Associate Coordinator of the Statistical Consulting Service, Institute for Social Research. Dr. Cribbie was a member of the 2002 - 2004 and 2005 - 2007 SPIDA organizing committees.

David Flora, is an Assistant Professor in the Department of Psychology at York University and the Coordinator of the Statistical Consulting Service. He received his Ph.D. 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.

John Fox, Department of Sociology, McMaster University and Associate Coordinator, Statistical Consulting Service, Institute for Social Research, and a member of York's 2002 - 2004 and 2005 - 2007 SPIDA organizing committees. Dr. Fox has long-standing and close contact with the Inter-University Consortium for Political and Social Research (ICPSR) at the University of Michigan at Ann Arbor. In addition to teaching ICPSR courses each summer for many years, he is a member of the Advisory Committee to the ICPSR.

Michael Friendly, Department of Psychology, York University and an Associate Coordinator of the Statistical Consulting Service, Institute for Social Research. Dr. Friendly has taught many short courses in the SCS and in the 2000 - 2004 SPIDA programs, and was a member of York's 2002 - 2004 and
2005 - 2007 SPIDA organizing committees.

Bryn Greer-Wootten, (Professor Emeritus) Department of Geography and Faculty of Environmental Studies, York University, Associate Coordinator, Statistical Consulting Service, and an Associate Director in the Institute for Social Research. Dr. Greer-Wootten was the principal organizer of the SPIDA sessions at York from 2004 to 2007.

Georges Monette, Department of Mathematics and Statistics, and past Coordinator of the Statistical Consulting Service, Institute for Social Research. Dr. Monette has organized and taught the short courses offered by the SCS for many years, especially several very successful courses on mixed models and longitudinal data analysis. Professor Monette was the principal organizer of the successful 2000 SPIDA at York University, and a member of York's 2002 - 2004 and
2005 - 2007 SPIDA organizing committees.

Andie Noack is an Assistant Professor in the Department of Sociology at Ryerson University, and a PhD candidate in Sociology at York University. Ms. Noack was previously employed as a Data Analyst at York University's Institute for Social Research, and has been involved in organizing the SPIDA program since 2004.