In its eleventh season this summer, ISR's Summer Program in Data Analysis focuses on linear models, beginning with “standard” regression, through generalized linear models and extending to mixed models, which incorporate two or more levels of data.

Linear models and their extension to generalized linear models are the workhorses of quantitative social research, as well as providing the basis for other, more advanced statistical techniques. The great advantage of the generalized linear models framework is that “standard” ordinary least squares (OLS) regression is the simplest case, and that logistic regression, Poisson regression and other complex models are easily incorporated. Particular attention will be paid to interpreting model results, including methods for visualizing models, and to "diagnostic" methods for determining how well a model represents the data. This part of the Program will be taught by Professor John Fox of McMaster University.

Linear models provide the basis for multilevel or mixed models, the topic of the second half of SPIDA 2010. Mixed models are useful for a wide range of data structures and research questions. They can be used for the analysis of hierarchical data, for example when students are nested in classes, which in turn are nested in schools, or when workers are nested within workplaces. The models provide simultaneous estimates of the differences between individuals, between higher-level units and of the way that those units affect individual differences.

Mixed models can also be used for the analysis of longitudinal data. Applying multilevel models, temporal trajectories, for example a sequence of health measurements over time, are conceptualized as “nested” within individual survey respondents. The shape of the trajectory reveals how an individual's health changes over time, in relation to her or his personal characteristics, such as age, income and family characteristics. Also it is possible to incorporate an additional level of “community” effects. This part of SPIDA will be taught by Professor Georges Monette of York University.

For the lectures and the daily computer lab sessions in SPIDA, we will be using R, an independent open source (i.e., free) statistical software package with wide-ranging pre-programmed statistical procedures and capacity for programming tailored statistical analyses. In addition, R is invaluable for generating informative high-quality graphics. SPIDA begins with a one-day introduction to R by Professor Glenn Stalker of York University. No previous knowledge of R is expected of participants. A non-profit enterprise based in the research community, R is rapidly becoming an alternative to the major commercial statistical packages for serious data analysis.

The 2010 Program is coordinated by Professors Michael Friendly, Bryn Greer-Wootten and Michael Ornstein. Previous SPIDA programs, which began in the summer of 2000, have mainly focussed on multilevel models and structural equation models.

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, Department of Psychology at York University and the Coordinator of the Statistical Consulting Service. Dr. Flora was an Instructor for both 2007 and 2008 SPIDA programs.

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 Summer Program.

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 2009.

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.

Andrea Noack, Department of Sociology at Ryerson University (PhD in Sociology from York University). Dr. 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.