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Axinn says data show incidents of sexual assault start at 'very young age'

Miech on 'generational forgetting' about drug-use dangers

Impacts of H-1B visas: Lower prices and higher production - or lower wages and higher profits?

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Call for papers: Conference on computational social science, April 2017, U-M

Sioban Harlow honored with 2017 Sarah Goddard Power Award for commitment to women's health

Post-doc fellowship in computational social science for summer or fall 2017, U-Penn

ICPSR Summer Program scholarships to support training in statistics, quantitative methods, research design, and data analysis

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Mon, Feb 13, 2017, noon:
Daniel Almirall, "Getting SMART about adaptive interventions"

Straightening the Seam Effect in Panel Surveys

Archived Abstract of Former PSC Researcher

Rips, L.J., Frederick G. Conrad, and S.S. Fricker. 2003. "Straightening the Seam Effect in Panel Surveys." Public Opinion Quarterly, 67:522-554.

Panel surveys, such as the Survey of Income and Program Participation and the Consumer Expenditure Survey, interview respondents every 3 or 4 months, but ask the respondents for monthly data. A typical finding in such surveys is that changes in responses to a question are relatively small for adjacent months within a reference period but much more abrupt for adjacent months across reference periods. Previous studies have attributed this "seam effect" either to underreporting of changes within the periods or to overreporting of changes across them. In the present studies, we attempt to distinguish these possibilities, using an experimental method that allows us to gauge respondents' accuracy as well as the number of times they change their answers. The studies produced seam effects and accompanying evidence for forgetting of queried information and bias toward constant responses within the reference period. In general, seam effects appear to increase as a function of the demands on memory. We also find that separating questions with the same content in the survey instrument decreases the seam effect. To account for these data, we propose a model in which respondents' answers are initially based on attempted memory retrieval. Inability to recall leads to (possibly biased) guessing or subsequent repetition of an earlier answer.

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