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Spatio-temporal modeling of legislation and votes

Publication ,  Journal Article
Wang, E; Salazar, E; Dunson, D; Carin, L
Published in: Bayesian Analysis
March 22, 2013

A model is presented for analysis of multivariate binary data with spatio-temporal dependencies, and applied to congressional roll call data from the United States House of Representatives and Senate. The model considers each legislator's constituency (location), the congressional session (time) of each vote, and the details (text) of each piece of legislation. The model can predict votes of new legislation from only text, while imposing smooth temporal evolution of legislator latent features, and correlation of legislators with adjacent constituencies. Additionally, the model estimates the number of latent dimensions required to represent the data. A Gibbs sampler is developed for posterior inference. The model is demonstrated as an exploratory tool of legislation and it performs well in quantitative comparisons to a traditional ideal-point model. © 2013 International Society for Bayesian Analysis.

Duke Scholars

Published In

Bayesian Analysis

DOI

EISSN

1931-6690

ISSN

1936-0975

Publication Date

March 22, 2013

Volume

8

Issue

1

Start / End Page

233 / 268

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 0104 Statistics
 

Citation

APA
Chicago
ICMJE
MLA
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Wang, E., Salazar, E., Dunson, D., & Carin, L. (2013). Spatio-temporal modeling of legislation and votes. Bayesian Analysis, 8(1), 233–268. https://doi.org/10.1214/13-BA810
Wang, E., E. Salazar, D. Dunson, and L. Carin. “Spatio-temporal modeling of legislation and votes.” Bayesian Analysis 8, no. 1 (March 22, 2013): 233–68. https://doi.org/10.1214/13-BA810.
Wang E, Salazar E, Dunson D, Carin L. Spatio-temporal modeling of legislation and votes. Bayesian Analysis. 2013 Mar 22;8(1):233–68.
Wang, E., et al. “Spatio-temporal modeling of legislation and votes.” Bayesian Analysis, vol. 8, no. 1, Mar. 2013, pp. 233–68. Scopus, doi:10.1214/13-BA810.
Wang E, Salazar E, Dunson D, Carin L. Spatio-temporal modeling of legislation and votes. Bayesian Analysis. 2013 Mar 22;8(1):233–268.

Published In

Bayesian Analysis

DOI

EISSN

1931-6690

ISSN

1936-0975

Publication Date

March 22, 2013

Volume

8

Issue

1

Start / End Page

233 / 268

Related Subject Headings

  • Statistics & Probability
  • 4905 Statistics
  • 0104 Statistics