An empirical likelihood-based method for comparison of treatment effects-Test of equality of coefficients in linear models

Haiyan Su, Hua Liang

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

To compare two treatment effects, which can be described as the difference of the parameters in two linear models, we propose an empirical likelihood-based method to make inference for the difference. Our method is free of the assumptions of normally distributed and homogeneous errors, and equal sample sizes. The empirical likelihood ratio for the difference of the parameters of interest is shown to be asymptotically chi-squared. Simulation experiments illustrate that our method outperforms the published ones. Our method is used to analyze a data set from a drug study.

Original languageEnglish
Pages (from-to)1079-1088
Number of pages10
JournalComputational Statistics and Data Analysis
Volume54
Issue number4
DOIs
StatePublished - 1 Apr 2010

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Empirical Likelihood
Treatment Effects
Linear Model
Equality
Coefficient
Experiments
Chi-squared
Likelihood Ratio
Simulation Experiment
Drugs
Sample Size

Cite this

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