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

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

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Highlights

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"

psc brown bag iconAggregation Problems

Jennifer Johnson-Hanks (Department of Demography, University of California, Berkeley)

03/11/2013, at noon in room 6050 ISR-Thompson.

Archived video available

Social science relies heavily on aggregation - that is, on moving from individual cases or instances to higher-order categories. This presentation argues that (1) basic theoretical claims are embedded in how we make up the aggregates that we study, (2) important phenomena may look radically different at different levels of aggregation, (3) aggregates may have certain characteristics that apply only at that aggregate level, and cannot be reduced to the characteristics of the constituent parts, and (4) sometimes the apparent characteristics of the aggregate are artifacts of a bad process of aggregation and what look like relationships are not in fact relationships at all. The variation in how relationships at the micro level are reflected at the macro, and vice versa, may be systematic and meaningful. That is, when we know something about the causal processes behind the variables that interest us, we may be able to predict what kinds of macro-micro patterns will emerge as we move across levels of aggregation.

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