Multiverse Analysis: Computational Methods for Robust Results - Couverture rigide

Young, Cristobal; Cumberworth, Erin

Couverture rigide

ISBN 10 : 1316518787 ISBN 13 : 9781316518786

Editeur : Cambridge University Press, 2025

Synopsis

There are many ways of conducting an analysis, but most studies show only a few carefully curated estimates. Applied research involves a complex array of analytical decisions, often leading to a 'garden of forking paths' where each choice can lead to different results. By systematically exploring how alternative analytical choices affect the findings, Multiverse Analysis reveals the full range of estimates that the data can support and uncovers insights that single-path analyses often miss. It shows which modelling decisions are most critical to the results and reveals how data and assumptions work together to produce empirical estimates. Focusing on intuitive understanding rather than complex mathematics, and drawing on real-world datasets, this book provides a step-by-step guide to comprehensive multiverse analysis. Go beyond traditional, single-path methods and discover how multiverse analysis can lead to more transparent, illuminating, and persuasive empirical contributions to science.

A propos du livre

À propos des auteurs

Cristobal Young is Associate Professor of Sociology at Cornell University. He received his PhD from Princeton University in 2010. His first book, The Myth of Millionaire Tax Flight: How Place Still Matters for the Rich, was published with Stanford University Press in 2017.

Erin Cumberworth is a sociologist who studies inequality and public policy. She received her Ph.D. from Stanford University in 2017.

Détails de l'édition

• Éditeur: Cambridge University Press
• Date d'édition: 2025
• Langue: anglais
• ISBN 10: 1316518787
• ISBN 13: 9781316518786
• Reliure: Relié
• Nombre de pages: 286
• Coordonnées du fabricant: Cambridge University Press; https://www.cambridge.org/; ; Via Honduras,15; Pomezia; Italia; 71; Italie