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1 - The Many Worlds of Analysis

from Part I - Introduction

Published online by Cambridge University Press:  28 February 2025

Cristobal Young  and
Erin Cumberworth
Cristobal Young
Affiliation:
Cornell University, New York
Erin Cumberworth
Affiliation:
Cornell University, New York
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Summary

A dataset does not speak for itself, and model assumptions can drive results just as much as the data. Limited transparency about model assumptions creates a problem of asymmetric information between analyst and reader. This chapter shows how we need better methods for robust results.

Keywords

multiverse analysisrobustnessasymmetric information
Type
Chapter
Information
Multiverse Analysis
Computational Methods for Robust Results
 , pp. 3 - 12
Publisher: Cambridge University Press
Print publication year: 2025

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