Multiverse Analysis: Computational Methods for Robust Results (Analytical Methods for Social Research) - Tapa blanda

Young, Cristobal

 
9781009009966: Multiverse Analysis: Computational Methods for Robust Results (Analytical Methods for Social Research)

Sinopsis

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.

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Acerca de los autores

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.

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Otras ediciones populares con el mismo título

9781316518786: Multiverse Analysis: Computational Methods for Robust Results (Analytical Methods for Social Research)

Edición Destacada

ISBN 10:  1316518787 ISBN 13:  9781316518786
Editorial: Cambridge University Press, 2025
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