Dynamic Ideal Point Models is a statistical methodology in political science that extends static ideal point estimation by incorporating temporal dynamics to capture how legislators' latent ideological preferences evolve over time.
19
Publications
3.3K
Citations
32
Authors
31
Institutions
Publications per year
2017–2026
7
Parents
Publications
19
1–5 of 19
Authors
32
- MB
5
h-index
- EV
4
h-index
- AS
2
h-index
- KI
1
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- JL
1
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1–5 of 32
Institutions
31
Georgetown University
Washington, United States
5 h-index
9 publications
3K citations
Walsh University
North Canton, United States
3 h-index
3 publications
1.3K citations
University of Chicago
Chicago, United States
2 h-index
2 publications
266 citations
Wuhan University
Wuhan, China
1 h-index
1 publications
43 citations
University of Illinois System
Urbana, United States
1 h-index
1 publications
42 citations
Hong Kong Polytechnic University
Hong Kong, Hong Kong
1 h-index
1 publications
43 citations
Oakland University
Rochester, United States
1 h-index
1 publications
13 citations
University of Southern California
Los Angeles, United States
1 h-index
1 publications
97 citations
1–8 of 31
Venues
- Political Analysis
4 publications · 1.3K citations
4
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- SSRN Electronic Journal
Repository · 2 publications · 238 citations
2
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- American Journal of Political Science
AJPS · 2 publications · 381 citations
2
h-index
- American Political Science Review
1 publications · 97 citations
1
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- Journal of Conflict Resolution
1 publications · 1.1K citations
1
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1–5