Summer Program in Data Analysis (SPIDA) 2010

June 2 – 10, 2010

DEADLINE FOR APPLICATIONS IS FEBRUARY 22, 2010

BURSARY FOR FULL TIME STUDENTS IS AVAILABLE

York's Summer Program in Data Analysis (SPIDA) is an eight-day series of
intensive lectures and workshops designed to train social science researchers
in the theory and practice of linear, generalized linear, and multilevel [or
mixed] models, as they are applied to hierarchical and longitudinal data,
typically generated by panel surveys.

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 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 into the generalized linear models framework. 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 [June 3 – 5].

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 establishments.
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 [June 7 – 10].

A typical day in the Program consists of a morning lecture, with a related
computer lab session in the afternoon. Computing will be done in R, an
independent open source (i.e., free) statistical software package that is of
great value for its 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 for non-R users, by Professor Glenn Stalker of York
University [June 2].

Most days also include a lunch-time speaker who will present an interesting
application of the techniques being taught during that day’s session.

Further details about the Program, including a complete timetable and course
descriptions, as well as information about program fees, residence
accomodations, and the application process are provided at our web-site:

http://www.isr.yorku.ca/spida2010/index.html

The DEADLINE for applications is February 22nd, 2010. 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
March 15th, 2010.

SPIDA is intended 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.

Full-time students are eligible for a modest fee bursary. Some financial support
is also available for applicants who live outside the Greater Toronto
Area to help cover the costs of travel and accommodation.

SPIDA is funded by the Canadian Initiative on Social Statistics, a co-operative
project of the Social Sciences and Humanities Research Council of
Canada and Statistics Canada.

For further inquiries about the Program, please contact Dr. Bryn Greer-Wootten
via spida@yorku.ca.