Survey data, both cross-sectional and longitudinal, now being collected
by government, health and social science organizations have increasingly
complex structures. Many methods of data analysis have already been
developed for cross-sectional surveys. Much work remains to be done.
Many newer surveys done by Statistics Canada involve longitudinal data
collection. The data from both cross-sectional and longitudinal surveys
are becoming increasingly available across Canada through the recently
created Statistics Canada Research Data Centres.
Statistics Canada has identified a pressing need for new methodologies
in view of their ongoing data collection efforts in these complex surveys.
The workshop will be devoted to the discussion of newly emerging methodologies
for the analysis of complex surveys. It is also intended that the workshop
will bring together academics who have both methodological and subject
matter research interests in complex survey data, and researchers from
Statistics Canada who have either a research interest in, or are "at
the front line" working with, these data on a daily basis.
Some of the themes that will be pursued include: (1) variance estimation
for complex without replacement sampling designs; (2) modeling of correlated
duration data from longitudinal surveys; (3) multi-level modeling of
survey data; and (4) item response theory for surveys. Graduate students
are encouraged to attend.