Quantile modeling for political research / Xiao Lu

Format:

Book

Author/Creator:

Lu, Xiao (Of Beijing da xue), author.

Series:

Elements in quantitative and computational methods for social science

Cambridge elements. Elements in quantitative and computational methods for the social sciences, 2398-4023

Language:

English

Subjects (All):

Political statistics.

Political science--Mathematical models.

Political science.

Quantile regression.

Physical Description:

1 online resource

Place of Publication:

Cambridge : Cambridge University Press, 2026

Summary:

"Quantile models are widely used across the natural and social sciences to analyze heterogeneous phenomena that conventional mean-based approaches often obscure. Yet, despite their growing importance in many disciplines, their adoption in political science has remained comparatively limited, in part because the field still lacks an accessible introduction tailored to its substantive questions and empirical practices. This Element addresses that gap by showing how quantile models can expand the methodological repertoire of political science and deepen our understanding of political phenomena. Combining methodological innovation with practical guidance, this Element introduces quantile models for both continuous and discrete response variables and illustrates their use with real-world political examples. All empirical applications are accompanied by publicly available data, code, and software, making the Element a useful resource for both teaching and research"-- Cambridge Core

Contents:

Quantile models for continuous responses

Quantile models for binary choices

Quantile models for multiple choices

A brief overview of other quantile methods

Notes:

Includes bibliographical references

Online resource; title from PDF title page (Cambridge Core, viewed July 6, 2026)

Other Format:

Print version: Lu, Xiao (Of Beijing da xue) Quantile modeling for political research

ISBN:

9781009606004

100960600X

9781009605991

1009605992

OCLC:

1592134092

Publisher Number:

CIPO000381751

Access Restriction:

Some versions: Open access versions available from some providers open access