Details
| Original language | English |
|---|---|
| Pages (from-to) | 645-656 |
| Number of pages | 12 |
| Journal | Biometrical journal |
| Volume | 43 |
| Issue number | 5 |
| Publication status | Published - 28 Aug 2001 |
Abstract
In the past many multiple comparison procedure were difficult to perform. Usually, such procedures can be traced back to studentized multiple contrast tests. Numerical difficulties restricted the use of the exact procedures to simple, commonly balanced, designs. Conservative approximations or simulation based approaches have been used in the general cases. However, new efforts and results in the past few years have led to fast and efficient computations of the underlying multidimensional integrals. Inferences for any finite set of linear functions of normal means are now numerically feasible. These include all-pairwise comparisons, comparisons with a control (including dose-response contrasts), multiple comparison with the best, etc. The article applies the numerical progress on multiple comparisons procedures for common balanced and unbalanced designs within the general linear model.
Keywords
- Multivariate t-distribution, Numerical computation, Studentized contrast tests
ASJC Scopus subject areas
- Mathematics(all)
- Statistics and Probability
- Decision Sciences(all)
- Statistics, Probability and Uncertainty
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In: Biometrical journal, Vol. 43, No. 5, 28.08.2001, p. 645-656.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - On the numerical availability of multiple comparison procedures
AU - Bretz, Frank
AU - Genz, Alan
AU - Hothorn, Ludwig A.
PY - 2001/8/28
Y1 - 2001/8/28
N2 - In the past many multiple comparison procedure were difficult to perform. Usually, such procedures can be traced back to studentized multiple contrast tests. Numerical difficulties restricted the use of the exact procedures to simple, commonly balanced, designs. Conservative approximations or simulation based approaches have been used in the general cases. However, new efforts and results in the past few years have led to fast and efficient computations of the underlying multidimensional integrals. Inferences for any finite set of linear functions of normal means are now numerically feasible. These include all-pairwise comparisons, comparisons with a control (including dose-response contrasts), multiple comparison with the best, etc. The article applies the numerical progress on multiple comparisons procedures for common balanced and unbalanced designs within the general linear model.
AB - In the past many multiple comparison procedure were difficult to perform. Usually, such procedures can be traced back to studentized multiple contrast tests. Numerical difficulties restricted the use of the exact procedures to simple, commonly balanced, designs. Conservative approximations or simulation based approaches have been used in the general cases. However, new efforts and results in the past few years have led to fast and efficient computations of the underlying multidimensional integrals. Inferences for any finite set of linear functions of normal means are now numerically feasible. These include all-pairwise comparisons, comparisons with a control (including dose-response contrasts), multiple comparison with the best, etc. The article applies the numerical progress on multiple comparisons procedures for common balanced and unbalanced designs within the general linear model.
KW - Multivariate t-distribution
KW - Numerical computation
KW - Studentized contrast tests
UR - http://www.scopus.com/inward/record.url?scp=0035641768&partnerID=8YFLogxK
U2 - 10.1002/1521-4036(200109)43:5<645::AID-BIMJ645>3.0.CO;2-F
DO - 10.1002/1521-4036(200109)43:5<645::AID-BIMJ645>3.0.CO;2-F
M3 - Article
AN - SCOPUS:0035641768
VL - 43
SP - 645
EP - 656
JO - Biometrical journal
JF - Biometrical journal
SN - 0323-3847
IS - 5
ER -