Mindenkit szeretettel várunk az MTA TK "Lendület" RECENS hálózati előadás-sorozatának következő alkalmára 2017. január 10-én (kedden), melyen Felix Elwert (Vilas Associate Professor of Sociology at the Department of Sociology, University of Wisconsin-Madison) tart előadást "Causal Graphs for Social Scientists” címmel.
Az előadás megrendezésére az MTA TK "Lendület" RECENS Kutatócsoport tárgyalótermében (1014 Budapest, Országház utca 30., Keresztszárny földszint) kerül sor 15:00-as kezdettel.
Az előadás kivonata:
Causal inference is threatened by a small army of biases. Some biases are obvious, others are not. This lecture introduces directed acyclic graphs (DAGs) to classify biases in causal inference into three distinct groups: overcontrol bias, confounding bias, and selection bias. This classification helps social scientists spot, understand, and eliminate biases at the design, data-collection, and analysis stages of their research. This lecture will introduce the basic principles of DAGs and use them to illustrate examples of bias across the social sciences.
Felix Elwert is Vilas Associate Professor of Sociology at the Department of Sociology, University of Wisconsin-Madison. He earned his PhD in Sociology at Harvard. He is the winner of the first Causality in Statistics Education Award from the American Statistical Association. His publications appeared among others in the Annual Review of Sociology, in the American Journal of Sociology, and in the American Sociological Review. His research advances the understanding of two interlocking areas of social inequality: the contextual drivers of inequality, including neighborhood, network, and family effects on one hand and the demography of inequality on the other. His work pursues a theory-driven approach to causal inference with a focus on problems of dynamic selection to understand how contexts and demography shape individual life chances, their distributions, and their transmission within and across generations.