Details
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 3865-3875 |
| Seitenumfang | 11 |
| Fachzeitschrift | Computational Statistics and Data Analysis |
| Jahrgang | 56 |
| Ausgabenummer | 12 |
| Frühes Online-Datum | 19 Mai 2012 |
| Publikationsstatus | Veröffentlicht - Dez. 2012 |
Abstract
In a typical toxicity bioassay, an untreated control group and several groups of increasing dosage are studied. The use of historical control data from previous trials provides additional information for statistical analysis. It is assumed that dichotomous response variables (e.g.; dead/alive) can be suitably analyzed through the comparison of binomial proportions, where any confounding effects on the observed rates are presumed to be absent. Binomial proportions from historical control groups are used to estimate the parameters of a beta prior distribution. Using this beta prior allows knowledge from the historical control data to be applied to a current bioassay. Although trend tests for this situation have been proposed, our main focus is directed towards the construction of simultaneous confidence intervals allowing for an interpretation both in terms of statistical significance and biological relevance. The performance of the proposed approach was investigated in simulation studies for a wide range of potential scenarios. In many cases, the new approach is more powerful and less conservative than a common approach. The method is illustrated by evaluating a long-term carcinogenicity example from the literature.
ASJC Scopus Sachgebiete
- Mathematik (insg.)
- Statistik und Wahrscheinlichkeit
- Mathematik (insg.)
- Computational Mathematics
- Informatik (insg.)
- Theoretische Informatik und Mathematik
- Mathematik (insg.)
- Angewandte Mathematik
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in: Computational Statistics and Data Analysis, Jahrgang 56, Nr. 12, 12.2012, S. 3865-3875.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung › Peer-Review
}
TY - JOUR
T1 - The use of historical controls in estimating simultaneous confidence intervals for comparisons against a concurrent control
AU - Kitsche, Andreas
AU - Hothorn, Ludwig A.
AU - Schaarschmidt, Frank
N1 - Funding Information: The work was partly supported by the German Science Foundation grant DfG-HO1687 . The authors are grateful to the Associate Editor and two anonymous referees for their numerous helpful comments on earlier drafts, which greatly improved this article.
PY - 2012/12
Y1 - 2012/12
N2 - In a typical toxicity bioassay, an untreated control group and several groups of increasing dosage are studied. The use of historical control data from previous trials provides additional information for statistical analysis. It is assumed that dichotomous response variables (e.g.; dead/alive) can be suitably analyzed through the comparison of binomial proportions, where any confounding effects on the observed rates are presumed to be absent. Binomial proportions from historical control groups are used to estimate the parameters of a beta prior distribution. Using this beta prior allows knowledge from the historical control data to be applied to a current bioassay. Although trend tests for this situation have been proposed, our main focus is directed towards the construction of simultaneous confidence intervals allowing for an interpretation both in terms of statistical significance and biological relevance. The performance of the proposed approach was investigated in simulation studies for a wide range of potential scenarios. In many cases, the new approach is more powerful and less conservative than a common approach. The method is illustrated by evaluating a long-term carcinogenicity example from the literature.
AB - In a typical toxicity bioassay, an untreated control group and several groups of increasing dosage are studied. The use of historical control data from previous trials provides additional information for statistical analysis. It is assumed that dichotomous response variables (e.g.; dead/alive) can be suitably analyzed through the comparison of binomial proportions, where any confounding effects on the observed rates are presumed to be absent. Binomial proportions from historical control groups are used to estimate the parameters of a beta prior distribution. Using this beta prior allows knowledge from the historical control data to be applied to a current bioassay. Although trend tests for this situation have been proposed, our main focus is directed towards the construction of simultaneous confidence intervals allowing for an interpretation both in terms of statistical significance and biological relevance. The performance of the proposed approach was investigated in simulation studies for a wide range of potential scenarios. In many cases, the new approach is more powerful and less conservative than a common approach. The method is illustrated by evaluating a long-term carcinogenicity example from the literature.
KW - Historical controls
KW - Simultaneous confidence intervals
KW - Toxicological bioassays
UR - http://www.scopus.com/inward/record.url?scp=84864130601&partnerID=8YFLogxK
U2 - 10.1016/j.csda.2012.05.010
DO - 10.1016/j.csda.2012.05.010
M3 - Article
AN - SCOPUS:84864130601
VL - 56
SP - 3865
EP - 3875
JO - Computational Statistics and Data Analysis
JF - Computational Statistics and Data Analysis
SN - 0167-9473
IS - 12
ER -