Activities Sponsored by the Survey Methods Section

• Workshop
• Invited Sessions
• Case Study
• 2005 Joint Statistical Meetings

Workshop on Survey Methods, June 12, 2005

Using Survey Data to Enhance Teaching and Research

Speakers:
* Chuck Humphrey, University of Alberta
* Gustave Goldmann, Statistics Canada
* Leslie Anne Keown, University of Calgary
* Bradley A. Corbett, University of Western Ontario

The workshop provides an introduction to some well-known Canadian surveys and focuses on (i) how to access and use existing sources of survey data; (ii) commonly used statistical tools in analyzing these data; and (iii) problems and challenges in using these data for teaching and research.

Invited Sessions

Special Invited Session: Bootstrapping in complex surveys

Organizer: C. Wu, University of Waterloo

Speaker:
* Randy R. Sitter (Simon Fraser University)

Discussant:
* J.N.K. Rao (Carleton University)

Invited Session I: Inference from multiple surveys and multiple frame surveys

Organizer: N. Prasad, University of Alberta

Speakers:
* Sharon Lohr (Arizona State University)
* Avi Singh (Statistics Canada)
* Changbao Wu (University of Waterloo)

Invited Session II: Extensions of policy-relevant analytical methods for complex survey data

Organizer: G. Roberts, Statistics Canada

Speakers:
* Irene Lu (York University)
* Norberto Pantoja (University of Waterloo)
* Qunshu Ren (Carleton University)

Invited Session III: Imputation

Organizer: E. Rancourt, Statistics Canada

Speakers:
* Joseph L. Schafer (Pennsylvania University)
* Tom Krenzke and David Judkins (Westat)
* Robert Kozak (Statistics Canada)

Invited Session IV: Model and design based inference for sample surveys

Organizer: N. Prasad, University of Alberta

Speakers:
* Milorad Kovacevic, David Binder and Georgia Roberts (Statistics Canada)
* Subhash Lele and Narasimha Prasad (University of Alberta)
* Andre Cyr, Alexander Davies and Claude Girard (Statistics Canada)

Case Study: Longitudinal Data Analysis

This case study introduces the students to the analysis of longitudinal data using several different approaches (repeated measures, time-varying covariates and growth curves to name a few) as well as introducing the student to the differences in model-based and design-based approaches to estimation. A sub-sample of the synthetic data file from the National Longitudinal Study on Children and Youth (NLSCY) is used to introduce the problems related to estimation and variance calculation in longitudinal surveys. Many issues relating to children?s behaviour and care are important concerns for Canadians and so the data set was created with the objective that the student confronts a realistic situation in a longitudinal study and assesses the best way in which to analyze and present the data.

2005 Joint Statistical Meetings, Minneapolis

Invited Session Sponsored by SSC and Organized by the Survey Methods Section

Enhancing Human Welfare Through Large Scale Surveys: The Canadian Story

Organizers: G. Roberts and C. Wu

Speakers:
* Mary E. Thompson (University of Waterloo)
* Michelle Simard (Statistics Canada)
* Michael H. Boyle (McMaster University)
* Yves Beland (Statistics Canada)