Details
| Original language | English |
|---|---|
| Pages (from-to) | 43-56 |
| Number of pages | 14 |
| Journal | Environmental and Ecological Statistics |
| Volume | 7 |
| Issue number | 1 |
| Publication status | Published - Mar 2000 |
Abstract
In most real data situations in the one-way design both the underlying distribution and the shape of the dose-response curve are a priori unknown. The power of a trend test strongly depends on both. However, tests which are routinely used to analyze toxicological assays must be robust. We use nonparametric tests with different scores-powerful for different distributions-and different contrasts-powerful for different shapes-and use the maximum of all test statistics as a new test statistic. Simulation results indicate that this maximum test, which is a nonparametric multiple contrast test, stabilizes the power for various shapes and distributions. The investigated tests are applied to the data of a toxicological assay.
Keywords
- Maximum test, Multiple contrast test, Nonparametric model, Toxicological assays, Unknown dose-response shape
ASJC Scopus subject areas
- Mathematics(all)
- Statistics and Probability
- Environmental Science(all)
- General Environmental Science
- Decision Sciences(all)
- Statistics, Probability and Uncertainty
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In: Environmental and Ecological Statistics, Vol. 7, No. 1, 03.2000, p. 43-56.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Robust trend tests with application to toxicology
AU - Neuhäuser, Markus
AU - Seidel, Dirk
AU - Hothorn, Ludwig A.
AU - Urfer, Wolfgang
PY - 2000/3
Y1 - 2000/3
N2 - In most real data situations in the one-way design both the underlying distribution and the shape of the dose-response curve are a priori unknown. The power of a trend test strongly depends on both. However, tests which are routinely used to analyze toxicological assays must be robust. We use nonparametric tests with different scores-powerful for different distributions-and different contrasts-powerful for different shapes-and use the maximum of all test statistics as a new test statistic. Simulation results indicate that this maximum test, which is a nonparametric multiple contrast test, stabilizes the power for various shapes and distributions. The investigated tests are applied to the data of a toxicological assay.
AB - In most real data situations in the one-way design both the underlying distribution and the shape of the dose-response curve are a priori unknown. The power of a trend test strongly depends on both. However, tests which are routinely used to analyze toxicological assays must be robust. We use nonparametric tests with different scores-powerful for different distributions-and different contrasts-powerful for different shapes-and use the maximum of all test statistics as a new test statistic. Simulation results indicate that this maximum test, which is a nonparametric multiple contrast test, stabilizes the power for various shapes and distributions. The investigated tests are applied to the data of a toxicological assay.
KW - Maximum test
KW - Multiple contrast test
KW - Nonparametric model
KW - Toxicological assays
KW - Unknown dose-response shape
UR - http://www.scopus.com/inward/record.url?scp=0342699498&partnerID=8YFLogxK
U2 - 10.1023/A:1009606812545
DO - 10.1023/A:1009606812545
M3 - Article
AN - SCOPUS:0342699498
VL - 7
SP - 43
EP - 56
JO - Environmental and Ecological Statistics
JF - Environmental and Ecological Statistics
SN - 1352-8505
IS - 1
ER -