Details
| Original language | English |
|---|---|
| Pages (from-to) | 710-721 |
| Number of pages | 12 |
| Journal | Statistics in medicine |
| Volume | 37 |
| Issue number | 5 |
| Publication status | Published - 5 Feb 2018 |
Abstract
We present an extension of multiple contrast tests for multiple endpoints to the case of missing values. The endpoints are assumed to be normally distributed and correlated and to have equal covariance matrices for the different treatments. Different multivariate t distributions will be applied, differing in endpoint-specific degrees of freedom. In contrast to competing methods, the familywise error type I is maintained in the strong sense in an admissible range, and the problem of different marginal errors type I is avoided. The information of all observations is exploited, thereby enabling a gain in power compared with a complete case analysis.
Keywords
- correlated endpoints, missing values, multiple contrast tests, multiplicity adjustment, multivariate t distribution
ASJC Scopus subject areas
- Medicine(all)
- Epidemiology
- Mathematics(all)
- Statistics and Probability
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In: Statistics in medicine, Vol. 37, No. 5, 05.02.2018, p. 710-721.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Multi-arm trials with multiple primary endpoints and missing values
AU - Hasler, Mario
AU - Hothorn, Ludwig A.
PY - 2018/2/5
Y1 - 2018/2/5
N2 - We present an extension of multiple contrast tests for multiple endpoints to the case of missing values. The endpoints are assumed to be normally distributed and correlated and to have equal covariance matrices for the different treatments. Different multivariate t distributions will be applied, differing in endpoint-specific degrees of freedom. In contrast to competing methods, the familywise error type I is maintained in the strong sense in an admissible range, and the problem of different marginal errors type I is avoided. The information of all observations is exploited, thereby enabling a gain in power compared with a complete case analysis.
AB - We present an extension of multiple contrast tests for multiple endpoints to the case of missing values. The endpoints are assumed to be normally distributed and correlated and to have equal covariance matrices for the different treatments. Different multivariate t distributions will be applied, differing in endpoint-specific degrees of freedom. In contrast to competing methods, the familywise error type I is maintained in the strong sense in an admissible range, and the problem of different marginal errors type I is avoided. The information of all observations is exploited, thereby enabling a gain in power compared with a complete case analysis.
KW - correlated endpoints
KW - missing values
KW - multiple contrast tests
KW - multiplicity adjustment
KW - multivariate t distribution
UR - http://www.scopus.com/inward/record.url?scp=85041307961&partnerID=8YFLogxK
U2 - 10.1002/sim.7542
DO - 10.1002/sim.7542
M3 - Article
C2 - 29108137
AN - SCOPUS:85041307961
VL - 37
SP - 710
EP - 721
JO - Statistics in medicine
JF - Statistics in medicine
SN - 0277-6715
IS - 5
ER -