Buch, Englisch, 286 Seiten, Format (B × H): 157 mm x 235 mm, Gewicht: 566 g
Buch, Englisch, 286 Seiten, Format (B × H): 157 mm x 235 mm, Gewicht: 566 g
Reihe: Analytical Methods for Social Research
ISBN: 978-1-316-51878-6
Verlag: Cambridge University Press
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.
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Part I. Introduction: 1. The Many Worlds of Analysis; 2. The Multiverse as a Philosophy of Science; Part II. The Computational Multiverse: 3. Hurricane Names: An Applied Introduction; 4. The Multiverse Algorithm; 5. Empirical Multiverses; 6. Influence Analysis and Scope Conditions; 7. Good and Bad Controls; 8. Some Alternative Approaches; Part III. Expanding the Multiverse: 9. Functional Form Robustness; 10. Data Processing: Invisible Decisions that Matter; 11. A Data-Processing Multiverse: Re-Analysis of Regnerus (2012) and Critics; 12. Retractions in Social Science: Mis-Adventures in Data Processing; 13. Weights in the Multiverse; 14. Conclusion; Appendix: Coding with MULTIVRS in Stata.