Slides from a presentation to a conference sponsored by the American Political Science Association on "Democracy Audits and Governmental Indicators", University of California, Berkeley, October 30-31, 2009.
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with Lynn Vavreck
Despite Barack Obama's momentum in the early phase of the Democratic primaries and caucuses, the process of selecting a nominee took longer than usual. Eight candidates were winnowed to two, but the remaining two were competitive until the last primary was held. Further, when it appeared Barack Obama would win the nomination, substantial numbers of Hillary Clinton supporters vowed to defect from the party and support the opposition in the general election. Momentum, it seems, got stuck. How do we explain this unusual string of events? Why were some people unwilling to join the Obama bandwagon once he emerged as a viable front-runner --- and utlimately, the nominee? In this paper we bring unique panel data to bear on questions about primary vote choice. While it is known that attitudes about race predict vote choice in partisan contests, we demonstrate that these attitudes interact with the race of the candidate to explain voters' choices and transitions among candidates even in an intra-party contest.
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with Joshua Clinton
A comparison of the Bayesian quadratic-normal approach to the analysis of roll call data with W-NOMINATE. Legislative Studies Quarterly, V34(4):593-621.

with Lynn Vavreck
Presentation in "Presidential Politics: Race, Class, Faith & Gender in the 2008 Election", Monday, November 10, 2008
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Report on surveys fielded in Australia and the United States ahead of the 2008 U.S. Presidential election. The Australian fieldwork was commissioned by the United States Studies Centre at the University of Sydney; the U.S. fieldwork is part of the Cooperative Campaign Analysis Project (Lynn Vavreck of UCLA and I are the principal investigators).
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Oxford Handbook of Political Methodology, Henry E. Brady, David Collier and Janet Box-Steffensmeier (eds). 2008. Oxford University Press: Oxford, UK. pp119-151.

with Joshua Clinton
We reassess the claim that Senator Barack Obama is the most liberal senator in 2007. National Journal said the same thing about John Kerry in 2003. Presentation to the Department of Political Science, University of Rochester
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with Shawn Treier
We apply formal, statistical measurement models to the Polity indicators, used widely in studies of international relations to measure democracy. In so doing, we make explicit the hitherto implicit assumptions underlying scales built using the Polity indicators. Modeling democracy as a latent variable allows us to assess the ``noise'' (measurement error) in the resulting measure. We show that this measurement error is considerable, and has substantive consequences when using a measure of democracy as an independent variable in cross-national statistical analysis. Our analysis suggests that skepticism as to the precision of the Polity democracy scale is well-founded, and that many researchers have been overly sanguine about the properties of the Polity democracy scale in applied statistical work. American Journal of Political Science, 2008, V52(1):201-217.

with Matthew S. Levendusky and Jeremy C. Pope
Many empirical studies of American politics, particularly legislative politics, are vitally dependent on measures of the partisanship of a district. We develop a measurement model for this quantity, estimating how Democratic (or, conversely, Republican) districts are in the absence of a election-specific, short-term forces, such as national-level swings specific to particular elections, incumbency advantage, and home-state effects in presidential elections. We estimate the model using readily available data: electoral returns and district-level demographic characteristics. We estimate the model with five decades of data (1952-2000), and describe how the distribution of district partisanship has changed over time, in response to population movements and redistricting, particularly via the creation of majority-minority districts. We validate the measure with analysis of Congressional roll call data, and show how to enrich this measure using other available indicators of district partisanship, such as survey data. Journal of Politics. July 2008. V70(3):736-753.
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with Peter Brent
We examine recent trends in electoral enrollment in Australia, which suggest that since the 2004 Federal election, enrollments have fallen as a share of the eligible population. Recent months have seen a marked increase in enrolment, but the disparity remains. We suggest some reasons as to why this has occured. Democratic Audit of Australia

In this short note I draw attention to R's abilities for data processing, and in particular, R's ``Perl-like'' abilities for parsing text. The application involves reading data from the web site of the California Secretary of State containing "real-time" updates of results from the 2006 congressional elections. In the zip file I provide a PDF document describing the R code that reads and processes the data, along with the R command file itself. The Political Methodologist. V14(2):11-15.
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with Matthew S. Levendusky and Jeremy C. Pope
We've been getting numerous requests for our estimates of district-level partisanship. Here we provide (1) estimates of district partisanship, one set per decade; (2) 2000 samples from the joint posterior density of district-level partisanship, one file per decade. Our partisanship scale runs in a Republican to Democratic direction (negative to positive), and is normalized to have mean zero and standard deviation one across districts. The zip file contains comma-delimited ascii files, with a header row. 37MB zip file.

Slides from a presentation made at the Social Science Methodology Conference, hosted by the Australian Consoritium for Social and Political Research, University of Sydney, Dec 10-13, 2006
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Data, R code, detailed instructions on the analysis appearing "The Most Liberal Senator?" PS: Political Science and Politics, 2004 V37(3): 805-811. The zip file contains a PDF file documenting the analysis, and two data sets (one an R binary object, the other a comma-delimited file) containing the roll call matrix from the U.S. Senate for National Journal's 62 "key votes" for 2003.
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with Alex Tahk and Christina Maimone; contributions from Achim Zeileis and Jim Fearon.
R classes and methods for the Bayesian analysis of roll call data (item-response models); elementary Bayesian statistics; maximum likelihood estimation of zero-inflated and hurdle models for count data; seats-votes curves; utility functions. Version 0.73. Available from the Comprehensive R Archive Network (CRAN) Package manual available for download here (below).
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with Paul M. Sniderman
Can citizens learn from talking politics with one another? To bring out the logic of deliberation, we focus on a simplified model of political discussion: a one-exchange argument. Our model rests on three conditions, all commonly satisfied in real life: (1) that only two alternatives are open for choice – support or opposition to a policy; (2) that as political sophistication increases, so too does the probability that citizens will choose the policy alternative more consonant with their most thoroughly considered view of the matter; and (3) that arguments on opposing sides of an issue are of equal quality. Taking advantage of a specially designed experiment embedded in a large public opinion survey in France, we find that the proportion of citizens choosing policy alternatives consonant with their more general ideological orientations does not increase over the course of our experiment. In the aggregate, we find that deliberation leads at least as many people to ideologically inconsistent positions as it helps people find their way to ideologically consistent positions. In this sense, we find that deliberation is for naught.
Journal of Politics. 2006. V68(2): 272-283 On-line appendix with measurement details available, below.
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with Neal Beck and Howard Rosenthal
We use a Bayesian dynamic linear model to track approval for George W.Bush over time. Our analysis deals with several issues that have been usually addressed separately in the extant literature. First, our analysis uses polling data collected at a higher frequency than is typical, using over 1,100 published national polls, and data on macro-economic conditions collected at the weekly level. By combining this much poll information, we are much better poised to examine the public's reactions to events over shorter time scales than can the typical analysis of approval that utilizes monthly or quarterly approval. Second, our statistical modeling explicitly deals with the sampling error of these polls, as well as the possibility of bias in the polls due to house effects. Indeed, quite aside from the question of ``what drives approval?'', there is considerable interest in the extent to which polling organizations systematically diverge from one another in assessing approval for the president. These bias parameters are not only necessary parts of any realistic model of approval that utilizes data from multiple polling organizations, but easily estimated via the Bayesian dynamic linear model.
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slides from a talk given to the annual meeting of the American Association for the Advancement of Science, St Louis, Missouri, February 20, 2006
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slides from a talk to the Method of Analysis in the Social Sciences Colloquium, Stanford University, March 7, 2006
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Poll results vary over the course of a campaign election and across polling organisations, making it difficult to track genuine changes in voter support. I present a statistical model that tracks changes in voter support over time by pooling the polls, and corrects for variation across polling organisations due to biases known as ‘house effects’. The result is a less biased and more precise estimate of vote intentions than is possible from any one poll alone. I use five series of polls fielded over the 2004 Australian federal election campaign (ACNielsen, the ANU/ninemsn online poll, Galaxy, Newspoll, and Roy Morgan) to generate daily estimates of the Coalition’s share of two-party preferred (2PP) and first preference vote intentions. Over the course of the campaign there is about a 4 percentage point swing to the Coalition in first preference vote share (and a smaller swing in 2PP terms), that begins prior to the formal announcement of the election, but is complete shortly after the leader debates. The ANU/ninemsn online poll and Morgan are found to have large and statistically significant biases, while, generally, the three phone polls have small and/or statistically insignificant biases, with ACNielsen and (in particular) Galaxy performing quite well in 2004. Australian Journal of Political Science. 2005. V40(4): 499-517. Replication archive and technical appendix available below.
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in Mortgage Nation: The 2004 Australian Election. Marian Simms and John Warhurst (eds). 2005. Perth, Western Australia: API Network/Curtin University of Technology. pp335-347.

slides from two workshop talks given at Pennsylvania State University, April 29-30, 2005
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slides from a presentation to the Voteworld conference, Institute for Governmental Studies, University of California, Berkeley, February 26, 2005
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slides from a talk given at the Seminar in Bayesian Inference in Econometrics and Statistics, Washington University in St Louis, August 1, 2005
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multiple regression analysis of rates of informality in the 2004 Australian House of Representatives election; divisional level data; key predictors are non-English speaking at home, ballot length (and the interaction of the two), along with tertiary education and an indicator for divisions in jurisdictions with optional preferential voting in their legislative elections.
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Op-ed piece comparing the two conservative victories in the 2004 U.S. and Australian elections; submitted to Dissent (www.dissent.com.au)
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Annual Reviews of Political Science. 2004. 7:483-505.

with Joshua Clinton and Doug Rivers
PS: Political Science and Politics. 2004. 37(3):805-811.
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Political Analysis 2004 12(4): 400-424.

with Joshua Clinton and Doug Rivers
American Political Science Review. 98(2):355-370.

The Political Methodologist. 2004. 12(2):6-11
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Sage Encyclopedia of Social Science Research Methods

with D. Sunshine Hillygus
American Journal of Political Science. 2003. 47(4):583-596.

The Political Methodologist. 2003. 11(2):20-22.
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The Cambridge Handbook of the Social Sciences in Australia. 2002. pp266-286.

a contribution to the International Encyclopedia of the Social and Behavioral Sciences (Elsevier)

Slides from a presentation to the Annual Meeting of the Australasian Political Studies Association, Brisbane, September 2001.
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Political Analysis. 2001. 9(3):227-241.

Political Analysis. 2000. 8(4):307-332.

American Journal of Political Science. 2000. 44(2):375-404.

Electoral Studies. 1999. 18:29-48.

Australian Journal of Political Science. 1998. 33(2): 167-186.

with Nathaniel Beck
American Journal of Political Science. 1998. 33:167-186.

Current Affairs Bulletin V73(3, October/November): 23-26
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Australian Journal of Political Science 30:347-55

with Gary Marks
Australian Journal of Political Science 29:277-91

British Journal of Political Science 24:319-57

Australian Journal of Political Science 27: 434-448