Details
| Originalsprache | Englisch |
|---|---|
| Aufsatznummer | 106837 |
| Fachzeitschrift | Computational Statistics and Data Analysis |
| Jahrgang | 142 |
| Ausgabenummer | 142 |
| Frühes Online-Datum | 16 Sept. 2019 |
| Publikationsstatus | Veröffentlicht - Feb. 2020 |
Abstract
The Rothman–Woodroofe symmetry test statistic is revisited on the basis of independent but not necessarily identically distributed random variables. The distribution-freeness if the underlying distributions are all symmetric and continuous is obtained. The results are applied for testing symmetry in a meta-analysis random effects model. The consistency of the procedure is discussed in this situation as well. A comparison with an alternative proposal from the literature is conducted via simulations. Real data are analyzed to demonstrate how the new approach works in practice.
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 142, Nr. 142, 106837, 02.2020.
Publikation: Beitrag in Fachzeitschrift › Artikel › Forschung
}
TY - JOUR
T1 - Rothman–Woodroofe symmetry test statistic revisited
AU - Gaigall, Daniel
PY - 2020/2
Y1 - 2020/2
N2 - The Rothman–Woodroofe symmetry test statistic is revisited on the basis of independent but not necessarily identically distributed random variables. The distribution-freeness if the underlying distributions are all symmetric and continuous is obtained. The results are applied for testing symmetry in a meta-analysis random effects model. The consistency of the procedure is discussed in this situation as well. A comparison with an alternative proposal from the literature is conducted via simulations. Real data are analyzed to demonstrate how the new approach works in practice.
AB - The Rothman–Woodroofe symmetry test statistic is revisited on the basis of independent but not necessarily identically distributed random variables. The distribution-freeness if the underlying distributions are all symmetric and continuous is obtained. The results are applied for testing symmetry in a meta-analysis random effects model. The consistency of the procedure is discussed in this situation as well. A comparison with an alternative proposal from the literature is conducted via simulations. Real data are analyzed to demonstrate how the new approach works in practice.
KW - Measurement error
KW - Meta-analysis
KW - Not identically distributed
KW - Random effects model
KW - Rothman–Woodroofe statistic
KW - Symmetry test
UR - http://www.scopus.com/inward/record.url?scp=85072297509&partnerID=8YFLogxK
U2 - 10.1016/j.csda.2019.106837
DO - 10.1016/j.csda.2019.106837
M3 - Article
VL - 142
JO - Computational Statistics and Data Analysis
JF - Computational Statistics and Data Analysis
SN - 0167-9473
IS - 142
M1 - 106837
ER -