Robust estimation and hypothesis testing of linear contrasts in analysis of covariance with Stochastic covariates

ŞENOĞLU B.

JOURNAL OF APPLIED STATISTICS, cilt.34, sa.2, ss.141-151, 2007 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 34 Sayı: 2
  • Basım Tarihi: 2007
  • Doi Numarası: 10.1080/02664760600994869
  • Dergi Adı: JOURNAL OF APPLIED STATISTICS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.141-151
  • Anahtar Kelimeler: generalized logistic, linear contrasts, modified likelihood, non-normality, robustness, stochastic covariates, NONNORMAL REGRESSION, EXPERIMENTAL-DESIGN, MAXIMUM-LIKELIHOOD
  • Ankara Üniversitesi Adresli: Evet

Özet

Estimators of parameters are derived by using the method of modified maximum likelihood (MML) estimation when the distribution of covariate X and the error e are both non-normal in a simple analysis of covariance (ANCOVA) model. We show that our estimators are efficient. We also develop a test statistic for testing a linear contrast and show that it is robust. We give a real life example.