Project Leader:
Dr. Changbao Wu , University of Waterloo
Survey data now being collected by many government, private, health and social science organizations have
increasingly complex structures precipitating an urgent demand for new statistical methodology to further
research in substantive areas. In cross-sectional studies, which are taken at one point in time, it is
typical to use very complex sampling designs, involving stratification and clustering as the components
of random sampling. There can also be complexities in the resulting data file due to the patterns of
nonresponse. In longitudinal studies, which follow individuals or groups of individuals over time, there
is additional complexity stemming from possible complex correlation structures induced by repeated
measurements on the same sampling unit, by irregularly spaced data and differing numbers of repeated
observations on individuals. This data type, with all its various complexities, is increasingly common
in substantive areas due to its power to infer causality, to separate individual and population trends
and to detect changes in time.
Canada is a world leader in sample survey methodology and many of Canada's top researchers in this area
are on this team. So too are some of Canada's top methodologists in longitudinal data analysis and
hierarchical models, and in addition, are U.S. based researchers from Westat Inc. This project involves
four overlapping groups of researchers with common research interests in the various complexities of
surveys. Within these groups are researchers from our non-academic partners in government, private
industry and biomedicine where this data type is created and utilized. Foremost among these is Statistics
Canada, widely regarded as one of the leading national statistical agencies in the world, noted for the
high quality of its data and its research and analysis. Statistics Canada has identified a pressing need
for new methodologies as its responds to the demands for a wide variety of survey initiatives. The second
group is from Westat Inc., a large U.S. survey methodology company in Washington, DC. that designs, collects,
analyzes and researches new methodologies for U.S. government agencies, international government agencies as
well as the private sector. Researchers from Westat involved in this project are interested in many aspects
of complex survey data, but are primarily focused on research in variance estimation, replication-based
methods, and issues of data disclosure. The third group is comprised of researchers in a number of subject
matter disciplines. These researchers are creating the demand for these new and more complex surveys, and
hence new methodologies. Increasingly, survey data are used to supplement existing databases in biomedicine,
which has lead to the involvement of such partners with a common research focus. Researchers at the Toronto
Rehabilitation Institute and the Institute for Clinical and Evaluative Sciences study the variability of
medical outcomes and interventions across institutions and jurisdictions. It is of interest to them to
incorporate related data housed in Statistics Canada.
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