Workshop on Mixed and Multilevel Modelling with R in Toronto

Summer Program In Data Analysis (SPIDA): May 24th – June 1st, 2012 In its thirteenth season this year, ISR’s Summer Program in Data Analysis focuses on linear models, beginning with “standard” regression through generalized linear models, and extending to mixed or multilevel models, linear and non-linear and generalized, which incorporate two or more hierarchical levels of data or longitudinal data structures. Linear models and their extension to generalized linear models (which unify linear models with other commonly employed statistical models, such as logistic and Poisson regression) are the workhorses of quantitative social research. Linear and generalized linear models additionally provide the basis for other, more advanced statistical techniques, including the mixed-effects models that are the focus of this year’s SPIDA. The first part of SPIDA will introduce participants to three foundational elements of the Program: (i) the R statistical computing environment; (ii) a review of linear models, including their implementation in R, “diagnostic” methods for checking models fit to data, and the elliptical geometry of least-squares regression; and (iii) introduce the generalized linear models framework and its implementation in R. 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 2012. 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 Fox. 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. Further details about the Program, including a complete timetable and course descriptions, as well as information about program fees, residence accommodations, and the application process are provided at our web-site: http://www.isr.yorku.ca/spida2012/index.html The DEADLINE for applications is February 13th, 2012. Because of high demand and the limited space available in the Program, it is necessary to select among applicants. Selection will be based on applicants’ previous experience in data analysis, as well as their statements of interest, but an effort will be made to represent all geographic regions and social science research interests. Applicants will be informed whether they have secured a place in the Program by February 20th, 2012. SPIDA is intended primarily for faculty, researchers and graduate and undergraduate students at Canadian universities, researchers and policy analysts in both public and not-for-profit organizations, and data librarians. Under the new funding arrangements for 2012, however, applications are invited from interested persons outside Canada. Full-time students are eligible for a modest fee bursary. For further inquiries about the Program, please contact Dr. Bryn Greer-Wootten via spida@yorku.ca.