A Bayesian Approach to Survivorship Bias in Historical Data Analysis [Ein Bayes'scher Ansatz zum Survivorship Bias in historischer Datenanalyse]

Wand, Tobias

Forschungsartikel (Zeitschrift) | Peer reviewed

Zusammenfassung

Datasets such as Seshat have allowed researchers to quantitatively test hypotheses about premodern societies and states with great success. Nevertheless, one has to consider potential sources of bias in the data such as a survivorship bias favouring the inclusion of long-lived over short-lived states. Bayesian methods can be used to complement standard modelling procedures to take this issue into account as is demonstrated by analysing the longevity distribution of premodern states.

Details zur Publikation

FachzeitschriftCliodynamics
Jahrgang / Bandnr. / Volume15
Ausgabe / Heftnr. / Issue1
Seitenbereich99-106
StatusVeröffentlicht
Veröffentlichungsjahr2024
Sprache, in der die Publikation verfasst istEnglisch
DOI10.21237/C7CLIO15163477
Link zum Volltexthttps://escholarship.org/uc/item/4b11h9k0
StichwörterCliodynamics; Bayesian Statistics; Historical Dynamics; Sociophysics; Data Science

Autor*innen der Universität Münster

Wand, Tobias
Center for Nonlinear Science (CeNoS)