RMST‐based multiple contrast tests in general factorial designs Article Swipe
Merle Munko
,
Marc Ditzhaus
,
Dennis Dobler
,
Jon Genuneit
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1002/sim.10017
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1002/sim.10017
Several methods in survival analysis are based on the proportional hazards assumption. However, this assumption is very restrictive and often not justifiable in practice. Therefore, effect estimands that do not rely on the proportional hazards assumption are highly desirable in practical applications. One popular example for this is the restricted mean survival time (RMST). It is defined as the area under the survival curve up to a prespecified time point and, thus, summarizes the survival curve into a meaningful estimand. For two‐sample comparisons based on the RMST, previous research found the inflation of the type I error of the asymptotic test for small samples and, therefore, a two‐sample permutation test has already been developed. The first goal of the present paper is to further extend the permutation test for general factorial designs and general contrast hypotheses by considering a Wald‐type test statistic and its asymptotic behavior. Additionally, a groupwise bootstrap approach is considered. Moreover, when a global test detects a significant difference by comparing the RMSTs of more than two groups, it is of interest which specific RMST differences cause the result. However, global tests do not provide this information. Therefore, multiple tests for the RMST are developed in a second step to infer several null hypotheses simultaneously. Hereby, the asymptotically exact dependence structure between the local test statistics is incorporated to gain more power. Finally, the small sample performance of the proposed global and multiple testing procedures is analyzed in simulations and illustrated in a real data example.
Related Topics
Concepts
Permutation (music)
Mathematics
Resampling
Test statistic
Sample size determination
Contrast (vision)
Statistics
Statistic
Statistical hypothesis testing
Null hypothesis
Multiple comparisons problem
Sample (material)
Econometrics
Type I and type II errors
Computer science
Artificial intelligence
Physics
Acoustics
Chromatography
Chemistry
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/sim.10017
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/sim.10017
- OA Status
- hybrid
- Cited By
- 10
- References
- 32
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4392148907
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4392148907Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1002/sim.10017Digital Object Identifier
- Title
-
RMST‐based multiple contrast tests in general factorial designsWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-02-25Full publication date if available
- Authors
-
Merle Munko, Marc Ditzhaus, Dennis Dobler, Jon GenuneitList of authors in order
- Landing page
-
https://doi.org/10.1002/sim.10017Publisher landing page
- PDF URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/sim.10017Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/sim.10017Direct OA link when available
- Concepts
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Permutation (music), Mathematics, Resampling, Test statistic, Sample size determination, Contrast (vision), Statistics, Statistic, Statistical hypothesis testing, Null hypothesis, Multiple comparisons problem, Sample (material), Econometrics, Type I and type II errors, Computer science, Artificial intelligence, Physics, Acoustics, Chromatography, ChemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
10Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 7, 2024: 2, 2023: 1Per-year citation counts (last 5 years)
- References (count)
-
32Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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