Estimation and hypothesis testing in the two-stage nested design under nonnormality

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Gedik Balay İ., Şenoğlu B.

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, cilt.92, sa.5, ss.998-1014, 2022 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 92 Sayı: 5
  • Basım Tarihi: 2022
  • Doi Numarası: 10.1080/00949655.2021.1982941
  • Dergi Adı: JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
  • Derginin Tarandığı İndeksler: 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
  • Sayfa Sayıları: ss.998-1014
  • Anahtar Kelimeler: Nested design, modified maximum likelihood, long-tailed symmetric, generalized logistic, robustness, MAXIMUM-LIKELIHOOD, REGRESSION, PARAMETERS, VARIANCE, ANOVA
  • Ankara Üniversitesi Adresli: Evet

Özet

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.