Spring School on Statistical Inference for Survey Data with Missing Observations
Introduction
Complex surveys play an important role in providing critical information for policy makers as well as the general public. Surveys and survey data are also widely used in many scientific areas, such as public health and social science research. How to best handle missing data in surveys has been one of the focal points of research in the past three decades, with the ultimate prize in achieving reliable and efficient use of information from complex surveys. Most household and social surveys around the world are experiencing higher refusal rates leading to appreciable amounts of missing data. Dropout or noncompliance in clinical trials may also lead to missing responses for some subjects. Missing data tend to induce biases and inefficient estimates. In the past two decades, there has been an extensive development of new methods and procedures to deal with missing data.
The proposed spring school is part of the activities of the Collaborative Research Team (CRT) on Statistical Inference for Complex Surveys with Missing Observations funded by the Canadian Statistical Science Institute (CANSSI). The spring school is envisioned as providing training for graduate students, postdoctoral fellows, statisticians working in the industry (for example, Statistics Canada) and young researchers interested in the topic of missing survey data. This training program is also designed to provide useful background and the current state-of-the-art research outputs on analysis of survey data with missing observations for students and postdoctoral fellows involved in the CANSSI CRT project. It is hoped that the spring school will serve as a starting or enhancing point for young statisticians to equip themselves with tools for analyzing missing survey data and to pursue research in this evolving field of both theoretical and practical importance.
Registration
Please register here.
All participants are required to pay the registration fee $185, which covers snacks, beverages and lunches for the scheduled breaks of each day.
Travel support
Limited travel support is available for graduate students and postdoctoral fellows. Send an email request to David Haziza <haziza@dms.umontreal.ca>.
Hotel information
Please refer to the Fields Institute housing page.
Sponsorship
The spring school is sponsored by the Fields Institute and the Canadian Statistical Sciences Institute (CANSSI).
Schedule
09:00 to 09:15 |
Coffee Break
|
09:15 to 10:30 |
Changbao Wu, University of Waterloo |
10:30 to 11:00 |
Coffee Break
|
11:00 to 12:15 |
Changbao Wu, University of Waterloo |
12:15 to 14:00 |
Lunch
|
14:00 to 15:15 |
David Haziza, Université de Montréal |
15:15 to 15:45 |
Coffee Break
|
15:45 to 17:00 |
Changbao Wu, University of Waterloo |
09:00 to 09:15 |
Coffee Break
|
09:15 to 10:30 |
Jae-kwang Kim, Iowa State University |
10:30 to 11:00 |
Coffee Break
|
11:00 to 12:15 |
Qixuan Chen, Columbia University |
12:15 to 14:00 |
Lunch
|
14:00 to 15:15 |
Qixuan Chen, Columbia University |
15:15 to 15:45 |
Coffee Break
|
15:45 to 17:00 |
David Haziza, Université de Montréal |
09:00 to 09:15 |
Coffee Break
|
09:15 to 10:30 |
David Haziza, Université de Montréal |
10:30 to 11:00 |
Coffee Break
|
11:00 to 12:15 |
Jae-kwang Kim, Iowa State University |
12:15 to 14:00 |
Lunch
|
14:00 to 15:15 |
Peisong Han, University of Waterloo |
15:15 to 15:45 |
Coffee Break
|
15:45 to 17:00 |
Olli Saarela, University of Toronto |
09:00 to 09:15 |
Coffee Break
|
09:15 to 10:30 | |
10:30 to 11:00 |
Coffee Break
|
11:00 to 12:15 | |
12:15 to 14:00 |
Lunch
|