Robust Estimation and Hypothesis Testing of Linear Contrasts in Analysis of Covariance with Stochastic Covariates

Birdal Senoğlu

Journal of Applied Statistics, 2007, vol. 34, issue 2, 141-151

Abstract: 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.

Keywords: Generalized logistic; linear contrasts; modified likelihood; non-normality; robustness; stochastic covariates (search for similar items in EconPapers)
Date: 2007
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DOI: 10.1080/02664760600994869

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