Testing the difference between two independent regression models |
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Authors: | Mohammad Reza Mahmoudi Marziyeh Mahmoudi Elaheh Nahavandi |
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Institution: | 1. Department of Statistics, College of Science, Fasa University, Fasa, Islamic Republic of Iranmahmoudi.m.r@fasau.ac.ir;3. School of Mathematical Sciences, Shahrood University of Technology, Shahrood, Islamic Republic of Iran;4. Department of Biology, College of Science, Shiraz University, Shiraz, Islamic Republic of Iran |
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Abstract: | ABSTRACTIn some situations, for example, in biology or psychology studies, we wish to determine whether the linear relationship between response variable and predictor variables differs in two populations. The analysis of the covariance (ANCOVA) or, equivalently, the partial F-test approaches are the commonly used methods. In this study, the asymptotic distribution for the difference between two independent regression coefficients was established. The proposed method was used to derive the asymptotic confidence set for the difference between coefficients and hypothesis testing for the equality of the two regression models. Then a simulation study was conducted to compare the proposed method with the partial F method. The performance of the new method was comparable with that of the partial F method. |
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Keywords: | Cramer's theorem Multiple regression Simulation Simultaneous inference Slutsky's theorem |
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