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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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Next Brown Bag

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

Use of Interviewer Judgments about Attributes of Selected Respondents in Post-Survey Adjustments for Unit Nonresponse: An Illustration with the National Survey of Family Growth

Publication Abstract

Groves, Robert M., James Wagner, and Emilia Peytcheva. 2007. "Use of Interviewer Judgments about Attributes of Selected Respondents in Post-Survey Adjustments for Unit Nonresponse: An Illustration with the National Survey of Family Growth." Joint Statistical Meetings Proceedings, Survey Research Methods,

Postsurvey adjustments based on propensity models are increasingly popular in survey sampling. After examining the how weighting classes based on discretized estimated propensities can act to reduce the mean square error of respondent-based estimates, it is straightforward to focus on the covariance of the estimated propensity, p, and the survey variables, y's. When propensities are related to the y variables, then adjustments are likely to alter the expected value of the adjusted estimates. Because of this fact, it is desirable to examine ways to collect on both respondents and nonrespondents information predictive of the y variables. We refer to these variables as z variables. This paper reports on one initial attempt to do so, in the context of the National Survey of Family Growth. It reviews the paradata structure of the National Survey of Family Growth and presents initial efforts to model such paradata in a useful way for postsurvey adjustment.

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