Most Downloaded Articles
- The Spread of Evidence-Poor Medicine via Flawed Social-Network Analysis by Lyons, Russell
- Why and When "Flawed" Social Network Analyses Still Yield Valid Tests of no Contagion by VanderWeele, Tyler J./ Ogburn, Elizabeth L. and Tchetgen Tchetgen, Eric J.
- A New Method for Deriving Global Estimates of Maternal Mortality by Wilmoth, John R./ Mizoguchi, Nobuko/ Oestergaard, Mikkel Z./ Say, Lale/ Mathers, Colin D./ Zureick-Brown, Sarah/ Inoue, Mie and Chou, Doris
- Improving Statistical Inference with Clustered Data by Harden, Jeffrey J.
- Measuring Elusive Populations with Bayesian Model Averaging for Multiple Systems Estimation: A Case Study on Lethal Violations in Casanare, 1998-2007 by Lum, Kristian/ Price, Megan/ Guberek, Tamy and Ball, Patrick
Elections 2012: Suppressing Fraud or Suppressing the Vote?
1U. Massachusetts Medical School, Quantitative Health Sciences, Worcester, MA, 01655 USA
2Dartmouth College, Mathematics, Hanover, NH, 03755, USA
Citation Information: Statistics, Politics and Policy. Volume 4, Issue 1, Pages 14–28, ISSN (Online) 2151-7509, ISSN (Print) 2194-6299, DOI: 10.1515/spp-2012-0002, January 2013
- Published Online:
Recent years have seen a wave of laws making it more difficult to vote in the United States. Their ostensible purpose is to prevent voting by persons not legally qualified, and thus to improve public confidence in electoral integrity. Are such laws in fact needed to address serious fraud problems? On the other hand, how many and what kinds of legitimate voters will be, or have been, disenfranchised by them? Is voter confidence positively, or negatively, affected by voter ID laws? This article surveys what is known about these issues and offers suggestions for how statisticians can contribute.