Estimation and hypothesis testing in the two-stage nested design under nonnormality
Journal of Statistical Computation and Simulation, vol.92, no.5, pp.998-1014, 2022 (SCI-Expanded, Scopus)
- Publication Type: Article / Article
- Volume: 92 Issue: 5
- Publication Date: 2022
- Doi Number: 10.1080/00949655.2021.1982941
- Journal Name: Journal of Statistical Computation and Simulation
- Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Business Source Elite, Business Source Premier, CAB Abstracts, Communication Abstracts, Metadex, Veterinary Science Database, zbMATH, Civil Engineering Abstracts
- Page Numbers: pp.998-1014
- Keywords: Nested design, modified maximum likelihood, long-tailed symmetric, generalized logistic, robustness
- Ankara Yıldırım Beyazıt University Affiliated: Yes
Abstract
© 2021 Informa UK Limited, trading as Taylor & Francis Group.The purpose of this paper is to develop robust and efficient estimators of the parameters in the two-stage nested design under nonnormality of error distribution using modified maximum likelihood methodology proposed by Tiku (Estimating the mean and standard deviation from a censored normal sample. Biometrika. 1967;54:155–165; Estimating the parameters of normal and logistic distributions from censored samples. Aust N Z J Stat. 1968;10:64–74). New test statistics based on proposed estimators are obtained to test the factor effects. An extensive Monte-Carlo simulation study is done for comparing the proposed estimators and the tests based on them with the corresponding normal theory solutions. Simulation results show that our solutions are more efficient and robust than the normal theory solutions. At the end of the study, we analyze two different real datasets taken from the literature.