Home > Publications . Search All . Browse All . Country . Browse PSC Pubs . PSC Report Series

PSC In The News

RSS Feed icon

Cheng finds marriage may not be best career option for women

Lam discusses youth population dynamics and economics in sub-Saharan Africa

Work by Bailey and Dynarski cited in NYT piece on income inequality

Highlights

Jeff Morenoff makes Reuters' Highly Cited Researchers list for 2014

Susan Murphy named Distinguished University Professor

Sarah Burgard and former PSC trainee Jennifer Ailshire win ASA award for paper

James Jackson to be appointed to NSF's National Science Board

Next Brown Bag


PSC Brown Bags will return in the fall

The 2010 Morris Hansen Lecture Dealing with Survey Nonresponse in Data Collection, in Estimation Discussion

Archived Abstract of Former PSC Researcher

Tourangeau, Roger. 2011. "The 2010 Morris Hansen Lecture Dealing with Survey Nonresponse in Data Collection, in Estimation Discussion." Journal of Official Statistics, 27(1): 29-32.

In dealing with survey nonresponse, statisticians need to consider (a) measures to be taken at the data collection stage, and (b) measures to be taken at the estimation stage. One may employ some form of responsive design. In the later stages of the data collection in particular, one tries to achieve an ultimate set of responding units that is "better balanced" or "more representative" than if no special effort is made. The concept of "balanced response set" introduced in this article extends the well-known idea of "balanced sample." A measure of "lack of balance" is proposed; it is a quadratic form relating to a multivariate auxiliary vector; its statistical properties are explored. But whether or not good balance has been achieved in the data collection, a compelling question remains at the estimation stage: How to achieve the most effective reduction of nonresponse bias in the survey estimates. Balancing alone may not help. The nonresponse adjustment effort is aided by a bias indicator, a product of three factors involving selected powerful auxiliary variables.

Browse | Search : All Pubs | Next