Details

Autor(en) / Beteiligte

• Elff, Martin
• Heisig, Jan Paul
• Schaeffer, Merlin
• Shikano, Susumu

Titel

Rejoinder to Daniel Stegmueller's Comments

Ist Teil von

• British journal of political science, 2021-01, Vol.51 (1), p.460-462

Ort / Verlag

Cambridge, UK: Cambridge University Press

Erscheinungsjahr

2021

Link zum Volltext

Quelle

Worldwide Political Science Abstracts

Beschreibungen/Notizen

• The main purpose of our extended re-run of Stegmueller's Monte Carlo analysis was to demonstrate that an increase in the Monte Carlo sample size or the variation of random seeds across simulation settings could correct for this problem. Since this design flaw is far from obvious – otherwise Stegmueller surely would have been able to avoid it – our goal was to ‘sensitise both the producers and readers of Monte Carlo simulations to the importance of such technicalities’ (Stegmueller 2020). [...]the Bernstein-von Mises theorem implies that any Bayesian posterior mode and the ML estimator of a correctly specified model will converge to each other as the sample size goes to infinity. [...]Stegmueller's results, our own findings and the broader related literature indicate that (a) the accuracy of inference may suffer if standard assumptions about the sampling distribution of estimators (such as asymptotic normality) do not apply and (b) such violations can easily go unnoticed if practitioners use the default settings of statistics packages without further reflection.