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Kruger says reports of phantom mobile phone ringing/vibrating more common among anxious

Stafford says too early to say whether stock market declines will curtail Americans' spending

Eisenberg says many colleges now train campus personnel to spot and refer troubled college students

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Call for papers: Conference on Integrating Genetics and the Social Sciences, Oct 21-22, 2016, CU-Boulder

PRB training program in policy communication for pre-docs. Application deadline, 2.28.2016

Call for proposals: PSID small grants for research on life course impacts on later life wellbeing

PSC News, fall 2015 now available

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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.

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