The Statistical Analysis of Roll Call Data

By Joshua D. Clinton, S. Jackman, Doug Rivers. American Political Science Review, 2004

1,121 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Political Science and International Relations

View Paper: https://www.semanticscholar.org/paper/bc17606aa1839b15c1a4a59614ccfb41c067adf7

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Citations in the corpus

Data Analysis Using Regression and Multilevel/Hierarchical Models: Understanding and summarizing the fitted models (2006, methodology): “Imbalance and lack of complete overlap have been discussed in many places; see, for example, Cochran and Rubin (1973), and King and Zeng (2006). The intervention for low-birth-weight children is described by Brooks-Gunn, Liaw, and Klebanov (1992) and Hill, Brooks-Gunn, and Waldfogel (2003). Imbalanc”
Apples and Oranges? The Problem of Equivalence in Comparative Research (2011, background): “…and the latent preference variableη jk , whereasτic can beinterpreted as “intensity”: the higher the threshold, the stronger 4IRT models are increasingly used in political science to measure ideal points of legislators (Clinton et al. 2004), judges (Martin and Quinn 2002), or voters (Jesse 2009).”
Enhancing the Validity and Cross-Cultural Comparability of Measurement in Survey Research (2003, methodology): “Similarly, in the literature on scaling roll calls, the values of only one or two legislators are typically used as anchors (e.g., Clinton, Jackman, and Rivers 2002 and Londregan 2000).”
poLCA: An R Package for Polytomous Variable Latent Class Analysis (2011, methodology): “The latent class model is similar to the latent trait model widely used for the estimation of voter and legislator “ideal points” (see, for example, Clinton, Jackman, and Rivers (2004)) in that both models assume the presence of an underlying, unobserved latent variable to explain patterns among…”
MCMCpack: Markov chain Monte Carlo in R (2011, background): “…social sciences is growing, and a number of researchers are using these approaches in substantive applications dealing with: deliberative bodies (Clinton, Jackman, and Rivers 2004; Martin and Quinn 2002), economic performance (Western 1998), income dynamics (Geweke and Keane 2000), legislative…”
Treating Words as Data with Error: Uncertainty in Text Statements of Policy Positions (2009, background): “Even when estimates of measurement error are provided—as is the case with surveys, expert surveys, and more recently, roll-call votes (e.g., Clinton, Jackman, and Rivers 2004)—political scientists rarely, if ever, make use of these estimates in the ways we encourage here.”
Spatial Voting in the 2004 Presidential Election (2009, background): “…dimensions 10 Although ideal point estimation techniques differ in areas such as the assumed shape of utility functions and error distributions (see Clinton, Jackman, and Rivers 2004, Heckman and Snyder 1997, and Poole and Rosenthal 1997), the resulting differences in the actual ideal point…”
How Party Polarization Affects Governance (2015, background): “Among the variety of alternative measures that have been developed (Bonica 2014, Clinton et al. 2004, Groseclose et al. 1999), the most prominent is NOMINATE, created by Poole & Rosenthal (1991, 1997).”
Build, Compute, Critique, Repeat: Data Analysis with Latent Variable Models (2014, background): “In quantitative political science, " ideal point models " are a onedimensional matrix factorization of legislative roll-call data (Clinton et al., 2004).”
Measuring Bias and Uncertainty in Ideal Point Estimates via the Parametric Bootstrap (2004, methodology): “In this section we compare the bootstrapped NOMINATE and QN estimator to the IDEAL model of Clinton et al. (2002). The IDEAL model begins with the same random utility model as QN.”
The Dynamics of State Policy Liberalism, 1936–2014 (2016, background): “The parameters in an LVM cannot be identified without restrictions on the parameter space (e.g., Clinton, Jackman, and Rivers 2004).”