The 2007 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. While SEMs have less flexibility in characterizing temporal trajectories than multilevel models, they 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.

Not only are these two approaches to longitudinal data complementary, in some circumstances it is possible to specify equivalent multilevel models and SEMs that give the same results. Drawing on the just-completed SPIDA experiences, David Flora will consider this comparison in more detail in opening the final event of the Program: SPIDA is pleased to welcome Professor Ken Bollen of the University of North Carolina, who will present our closing Symposium on June 14th: Topics in Random Effects Models for Longitudinal Data.

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 2007 Program, coordinated by Professors Michael Friendly, Bryn Greer-Wootten and Michael Ornstein, can be contrasted to earlier SPIDA programs, which began in the summer 2000. Previously, we have concentrated largely on either multilevel models or SEMs. Bringing the two approaches together in the same Program is this year’s innovation.

The proposal for this 2005 – 2007 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 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 the Statistical Consulting Service, Institute for Social Research. Dr. Cribbie was a member of the 2002 - 2004 SPIDA organizing committee.

Thomas F. Crossley, Department of Economics, McMaster University. The principal applicant for York’s successful Data Training School application in 2001, Dr. Crossley is a member of the Advisory Committee, Workplace and Employee Survey and of the Advisory Committee on Labour and Income Statistics (ACLIS) at Statistics Canada.

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 SPIDA organizing committee. 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 SPIDA organizing committee.

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 2006.

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.

Dr. Karen Robson was appointed to the Department of Sociology, York University, in 2004. A specialist in survey research, she has taught at the University of Essex Summer School (including teaching in Bosnia and Albania), since 2001.