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Pitfalls and potentials in simulation studies: Questionable research practices in comparative simulation studies allow for spurious claims of superiority of any method
被引:15
作者:
Pawel, Samuel
[1
,2
]
Kook, Lucas
[1
]
Reeve, Kelly
[1
]
机构:
[1] Univ Zurich, Epidemiol Biostat & Prevent Inst, Ctr Reproducible Sci, Zurich, Switzerland
[2] Univ Zurich, Epidemiol Biostat & Prevent Inst, Ctr Reproducible Sci, Hirschengraben 84, CH-8001 Zurich, Switzerland
关键词:
benchmarking studies;
Monte Carlo experiments;
overoptimism;
replicability;
reproducibility;
transparency;
REGULARIZATION PATHS;
ADAPTIVE LASSO;
DESIGN;
SELECTION;
BLIND;
D O I:
10.1002/bimj.202200091
中图分类号:
Q [生物科学];
学科分类号:
07 ;
0710 ;
09 ;
摘要:
Comparative simulation studies are workhorse tools for benchmarking statistical methods. As with other empirical studies, the success of simulation studies hinges on the quality of their design, execution, and reporting. If not conducted carefully and transparently, their conclusions may be misleading. In this paper, we discuss various questionable research practices, which may impact the validity of simulation studies, some of which cannot be detected or prevented by the current publication process in statistics journals. To illustrate our point, we invent a novel prediction method with no expected performance gain and benchmark it in a preregistered comparative simulation study. We show how easy it is to make the method appear superior over well-established competitor methods if questionable research practices are employed. Finally, we provide concrete suggestions for researchers, reviewers, and other academic stakeholders for improving the methodological quality of comparative simulation studies, such as preregistering simulation protocols, incentivizing neutral simulation studies, and code and data sharing.
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页数:19
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