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.