Details
| Original language | English |
|---|---|
| Pages (from-to) | 899-909 |
| Number of pages | 11 |
| Journal | Biometrical journal |
| Volume | 40 |
| Issue number | 8 |
| Publication status | Published - 19 Apr 1999 |
Abstract
Jonckheere's test is a frequently used nonparametric trend test for the evaluation of preclinical studies and clinical dose-finding trials. In this paper, a modification of Jonckheere's test is proposed. If the exact permutation distribution is used for inference, the modified test can fill out the level of the type I error in a much more complete way and is substantially more powerful than the common Jonckheere test. If the asymptotic normality is used for inference, the modified test is slightly more powerful. In addition, a maximum test is investigated which is more robust concerning an a priori unknown dose-response shape. The robustness is advantageous, especially in a closed testing procedure. The different tests are applied to two example data sets.
Keywords
- Closed testing procedure, Jonckheere's trend test, Maximum test, Unknown dose-response shape
ASJC Scopus subject areas
- Mathematics(all)
- Statistics and Probability
- Decision Sciences(all)
- Statistics, Probability and Uncertainty
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In: Biometrical journal, Vol. 40, No. 8, 19.04.1999, p. 899-909.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Nonparametric tests for trend
T2 - Jonckheere's test, a modification and a maximum test
AU - Neuhäuser, Markus
AU - Liu, Ping Yu
AU - Hothorn, Ludwig A.
PY - 1999/4/19
Y1 - 1999/4/19
N2 - Jonckheere's test is a frequently used nonparametric trend test for the evaluation of preclinical studies and clinical dose-finding trials. In this paper, a modification of Jonckheere's test is proposed. If the exact permutation distribution is used for inference, the modified test can fill out the level of the type I error in a much more complete way and is substantially more powerful than the common Jonckheere test. If the asymptotic normality is used for inference, the modified test is slightly more powerful. In addition, a maximum test is investigated which is more robust concerning an a priori unknown dose-response shape. The robustness is advantageous, especially in a closed testing procedure. The different tests are applied to two example data sets.
AB - Jonckheere's test is a frequently used nonparametric trend test for the evaluation of preclinical studies and clinical dose-finding trials. In this paper, a modification of Jonckheere's test is proposed. If the exact permutation distribution is used for inference, the modified test can fill out the level of the type I error in a much more complete way and is substantially more powerful than the common Jonckheere test. If the asymptotic normality is used for inference, the modified test is slightly more powerful. In addition, a maximum test is investigated which is more robust concerning an a priori unknown dose-response shape. The robustness is advantageous, especially in a closed testing procedure. The different tests are applied to two example data sets.
KW - Closed testing procedure
KW - Jonckheere's trend test
KW - Maximum test
KW - Unknown dose-response shape
UR - http://www.scopus.com/inward/record.url?scp=0040581534&partnerID=8YFLogxK
U2 - 10.1002/(SICI)1521-4036(199812)40:8<899::AID-BIMJ899>3.0.CO;2-9
DO - 10.1002/(SICI)1521-4036(199812)40:8<899::AID-BIMJ899>3.0.CO;2-9
M3 - Article
AN - SCOPUS:0040581534
VL - 40
SP - 899
EP - 909
JO - Biometrical journal
JF - Biometrical journal
SN - 0323-3847
IS - 8
ER -