Division of the Humanities and Social Sciences California Institute of Technology Pasadena, California 91125 Quantiles and Medians

Nber Working Paper Series Experimenting with Measurement Error: Techniques with Applications to the Caltech Cohort Study

Measurement error is ubiquitous in experimental work. It leads to imperfect statistical controls, attenuated estimated effects of elicited behaviors, and biased correlations between characteristics. We develop simple statistical techniques for dealing with experimental measurement error. These techniques are applied to data from the Caltech Cohort Study, which conducts repeated incentivized sur...

Division of the Humanities and Social Sciences California Institute of Technology Pasadena, California 91125 on Incentives and Updating in Agent Based Models

Division of the Humanities and Social Sciences California Institute of Technology Pasadena, California 91125 the Fcc Rules for the 700mhz Auction: a Potential Disaster

Division of the Humanities and Social Sciences California Institute of Technology Pasadena, California 91125 Gn the Meaning of the Preponderance Test in Judicial Regulation of Chemical Hazard

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Peter Sokol-Hessner, Colin F. Camerer, and Elizabeth A. Phelps Division of the Humanities and Social Sciences (HSS), California Institute of Technology, Division of the Humanities and Social Sciences (HSS) and Computational and Neural Systems (CNS), California Institute of Technology, 1200 E. California Blvd., Pasadena, CA 91125, USA, and Department of Psychology, New York University, 6 Washing...

Division of the Humanities and Social Sciences California Institute of Technology Pasadena, California 91125 Aggregation and Dynamics of Survey Responses: the Case of Presidential Approval

In this paper we critique much of the empirical literature on the important political science concept of presidential approval. Much of the recent research on presidential approval has focused on the dynamic nature of approval; arguments have raged about whether presidential approval is integrated, co-integrated, or fractionally integrated. We argue that none of these time-series concepts, impo...