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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"

Nonresponse rates and nonresponse bias in household surveys

Archived Abstract of Former PSC Researcher

Groves, Robert M. 2006. "Nonresponse rates and nonresponse bias in household surveys." Public Opinion Quarterly, 70(5): 646-675.

Many surveys of the U.S. household population are experiencing higher refusal rates. Nonresponse can, but need not, induce nonresponse bias in survey estimates. Recent empirical findings illustrate cases when the linkage between nonresponse rates and nonresponse biases is absent. Despite this, professional standards continue to urge high response rates. Statistical expressions of nonresponse bias can be translated into causal models to guide hypotheses about when nonresponse causes bias. Alternative designs to measure nonresponse bias exist, providing different but incomplete information about the nature of the bias. A synthesis of research studies estimating nonresponse bias shows the bias often present. A logical question at this moment in history is what advantage probability sample surveys have if they suffer from high nonresponse rates. Since postsurvey adjustment for nonresponse requires auxiliary variables, the answer depends on the nature of the design and the quality of the auxiliary variables.

DOI:10.1093/poq/nfl033 (Full Text)

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