자료유형  

 학위논문

Control Number  

0017163737

International Standard Book Number  

9798342116053

Dewey Decimal Classification Number  

658.152

Main Entry-Personal Name  

Handan-Nader, Cassandra.

Publication, Distribution, etc. (Imprint  

[S.l.] : Stanford University., 2024

Publication, Distribution, etc. (Imprint  

Ann Arbor : ProQuest Dissertations & Theses, 2024

Physical Description  

182 p.

General Note  

Source: Dissertations Abstracts International, Volume: 86-04, Section: A.

General Note  

Advisor: Grimmer, Justin.

Dissertation Note  

Thesis (Ph.D.)--Stanford University, 2024.

Summary, Etc.  

요약Latent variables factor prominently into theoretical models of political conflict, and estimates of latent variables using latent variable models often appear in empirical political science research. This dissertation innovates on classic latent measurement methodology in three distinct scenarios. The first chapter proposes a supervised measurement model to replace the prevailing unsupervised estimator for partisan polarization in the U.S. Congress using ideal points. The second chapter suggests a computationally efficient method of detection and removal for nuisance block and near-block structures that exert a disproportionate influence on correspondence analysis and related latent measurement models. The third chapter develops a two-step methodology of information retrieval and dimensionality reduction for extracting policy viewpoints from large text datasets.

Subject Added Entry-Topical Term  

Fund raising.

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Nominations.

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Bipartisanship.

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Regulation.

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Internet access.

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Politics.

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Legislators.

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Neural networks.

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Contingency tables.

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Eigenvalues.

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Civil war.

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Partisanship.

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20th century.

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Markov analysis.

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Elections.

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Web studies.

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Military studies.

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Political science.

Added Entry-Corporate Name  

Stanford University.

Host Item Entry  

Dissertations Abstracts International. 86-04A.

Electronic Location and Access  

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Control Number  

joongbu:657564