Scholars of political behavior increasingly embed experimental designs in opinion surveys by randomly assigning respondents alternative versions of questionnaire items. Such experiments have major advantages: they are simple to implement and they dodge some of the difficulties of making inferences from conventional survey data. But survey experiments are no panacea. We identify problems of inference associated with typical uses of survey experiments in political science and highlight a range of difficulties, some of which have straightforward solutions within the survey-experimental approach and some of which can be dealt with only by exercising greater caution in interpreting findings and bringing to bear alternative strategies of research.

This paper pursues a number of theoretical explorations and conjectures pertaining to the uncovered set in spatial voting games. It was stimulated by the article “The Uncovered Set and the Limits of Legislative Action” by W. T. Bianco, I. Jeliazkov, and I. Sened (2004, Political Analysis 12:256—78) that employed a grid-search computational algorithm for estimating the size, shape, and location of the uncovered set, and it has been greatly facilitated by access to the CyberSenate spatial voting software being developed by Joseph Godfrey. I bring to light theoretical considerations that account for important features of the Bianco, Jeliazkov, and Sened results (e.g., the straight-line boundaries of uncovered sets displayed in some of their figures, the “unexpectedly large” uncovered sets displayed in other figures, and the apparent sensitivity of the location of uncovered sets to small shifts in the relative sizes of party caucuses) and present theoretical insights of more general relevance to spatial voting theory.

When respondents use the ordinal response categories of standard survey questions in different ways, the validity of analyses based on the resulting data can be biased. Anchoring vignettes is a survey design technique, introduced by King et al. (2004, Enhancing the validity and cross-cultural comparability of measurement in survey research. American Political Science Review 94 [February]: 191–205), intended to correct for some of these problems. We develop new methods both for evaluating and choosing anchoring vignettes and for analyzing the resulting data. With surveys on a diverse range of topics in a range of countries, we illustrate how our proposed methods can improve the ability of anchoring vignettes to extract information from survey data, as well as saving in survey administration costs.

In this study, we propose a model of individual voter behavior that can be applied to aggregate data at the district (or precinct) levels while accounting for differences in political preferences across districts and across voters within each district. Our model produces a mapping of the competing candidates and electoral districts on a latent “issues” space that describes how political preferences in each district deviate from the average voter and how each candidate caters to average voter preferences within each district. We formulate our model as a random-coefficients nested logit model in which the voter first evaluates the candidates to decide whether or not to cast his or her vote, and then chooses the candidate who provides him or her with the highest value. Because we allow the random coefficient to vary not only across districts but also across unobservable voters within each district, the model avoids the Independence of Irrelevant Alternatives Assumption both across districts and within each district, thereby accounting for the cannibalization of votes among similar candidates within and across voting districts. We illustrate our proposed model by calibrating it to the actual voting data from the first stage of a two-stage state governor election in the Brazilian state of Santa Catarina, and then using the estimates to predict the final outcome of the second stage.

Poole's (2000, Non-parametric unfolding of binary choice data. Political Analysis 8:211–37) nonparametric Optimal Classification procedure for binary data produces misleading rank orderings when applied to the modern House of Commons. With simulations and qualitative evidence, we show that the problem arises from the government-versus-opposition nature of British (Westminster) parliamentary politics and the strategic voting that is entailed therein. We suggest that political scientists think seriously about strategic voting in legislatures when interpreting results from such techniques.