This paper considers the possible effects of making inferences about individuals from aggregate data. It assumes a knowledge of regression analysis, and explores the utility of techniques designed to make the inferences in causal modelling more reliable, including a comparison between ecological regression models and ecological correlation.
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Professor Langbein teaches quantitative methods, program evaluation, policy analysis, and public choice. Her research fields include: theories of bureaucratic discretion, productivity, principal-agent models, social capital, and cooperation in the workplace; theories of influence of interest groups in Congress and the bureaucracy; empirical applications in various policy areas, including the environment, education, defense, housing, criminal justice (death penalty and police), and corruption. Her articles have appeared in numerous journals on politics, economics, policy analysis and public administration. Her most recent publications examine the consequences of varying levels of discretion in federal agencies, and the World Bank's measurement of corruption in countries.
Allan J. Lichtman received his PhD from Harvard University in 1973 with a specialty in modern American history and quantitative methods. He became an Assistant Professor of History at American University in 1973 and a Full Professor in 1980. He was the recipient of the Scholar/Teacher of the year award for 1992-93. He has published seven books and several hundred popular and scholarly articles. He has lectured in the US and internationally and provided commentary for major US and foreign networks and leading newspapers and magazines across the world. He has been an expert witness in more than 75 civil and voting rights cases. His book, White Protestant Nation: The Rise of the American Conservative Movement was a finalist for the National Book Critics Circle Award in nonfiction. His prediction system, the Keys to the White House, has correctly predicted the outcomes of all US presidential elections since 1984.
Explores the utility of techniques designed to make the inferences in causal modeling more reliable, including a comparison between ecological regression models and ecological correlation.
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