Replicability of simulation studies for the investigation of statistical methods: the RepliSims project Article Swipe
Kim Luijken
,
Adolf W. Lohmann
,
Udi Alter
,
J. Claramunt Gonzalez
,
Felix J. Clouth
,
Jessica L. Fossum
,
L. Hesen
,
A. H. J. Huizing
,
J. Α. Α. Ketelaar
,
Amanda Kay Montoya
,
Linda Nab
,
R. C. C. Nijman
,
Bas B. L. Penning de Vries
,
Tristan Tibbe
,
Alex Wang
,
Rolf H. H. Groenwold
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1098/rsos.231003
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1098/rsos.231003
Results of simulation studies evaluating the performance of statistical methods can have a major impact on the way empirical research is implemented. However, so far there is limited evidence of the replicability of simulation studies. Eight highly cited statistical simulation studies were selected, and their replicability was assessed by teams of replicators with formal training in quantitative methodology. The teams used information in the original publications to write simulation code with the aim of replicating the results. The primary outcome was to determine the feasibility of replicability based on reported information in the original publications and supplementary materials. Replicasility varied greatly: some original studies provided detailed information leading to almost perfect replication of results, whereas other studies did not provide enough information to implement any of the reported simulations. Factors facilitating replication included availability of code, detailed reporting or visualization of data-generating procedures and methods, and replicator expertise. Replicability of statistical simulation studies was mainly impeded by lack of information and sustainability of information sources. We encourage researchers publishing simulation studies to transparently report all relevant implementation details either in the research paper itself or in easily accessible supplementary material and to make their simulation code publicly available using permanent links.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1098/rsos.231003
- OA Status
- gold
- Cited By
- 10
- References
- 59
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4390929439
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4390929439Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1098/rsos.231003Digital Object Identifier
- Title
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Replicability of simulation studies for the investigation of statistical methods: the RepliSims projectWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-01-01Full publication date if available
- Authors
-
Kim Luijken, Adolf W. Lohmann, Udi Alter, J. Claramunt Gonzalez, Felix J. Clouth, Jessica L. Fossum, L. Hesen, A. H. J. Huizing, J. Α. Α. Ketelaar, Amanda Kay Montoya, Linda Nab, R. C. C. Nijman, Bas B. L. Penning de Vries, Tristan Tibbe, Alex Wang, Rolf H. H. GroenwoldList of authors in order
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https://doi.org/10.1098/rsos.231003Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1098/rsos.231003Direct OA link when available
- Concepts
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Computer science, Replication (statistics), Code (set theory), Data science, Visualization, Empirical research, Information retrieval, Data mining, Statistics, Programming language, Mathematics, Set (abstract data type)Top concepts (fields/topics) attached by OpenAlex
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10Total citation count in OpenAlex
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2025: 7, 2024: 3Per-year citation counts (last 5 years)
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59Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| primary_location.raw_source_name | Royal Society Open Science |
| primary_location.landing_page_url | https://doi.org/10.1098/rsos.231003 |
| publication_date | 2024-01-01 |
| publication_year | 2024 |
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