Robust Estimation and Hypothesis Testing of Linear Contrasts in Analysis of Covariance with Stochastic Covariates
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.
Year of publication: |
2007
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Authors: | Senoğlu, Birdal |
Published in: |
Journal of Applied Statistics. - Taylor & Francis Journals, ISSN 0266-4763. - Vol. 34.2007, 2, p. 141-151
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Publisher: |
Taylor & Francis Journals |
Subject: | Generalized logistic | linear contrasts | modified likelihood | non-normality | robustness | stochastic covariates |
Saved in:
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