Maximum Likelihood Ratio based small-sample tests for random coefficients in linear regression
AbstractTwo small-sample tests for random coefficients in linear regression are derived from the Maximum Likelihood Ratio. The first test has previously been proposed for testing equality of fixed effects, but is here shown to be suitable also for random coefficients. The second test is based on the multiple coefficient of determination from regressing the observed subject means on the estimated slopes. The properties and relations of the tests are examined in detail, followed by a simulation study of the power functions. The two tests are found to complement each other depending on the study design: The first test is preferred for a large number of observations from a small number of subjects, and the second test is preferred for the opposite situation. Finally, the robustness of the tests to violations of the distributional assumptions is examined.
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Bibliographic InfoPaper provided by University of Gothenburg, Department of Economics in its series Working Papers in Economics with number 102.
Length: 21 pages
Date of creation: 25 Aug 2003
Date of revision:
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Exact test; Hypothesis test; Maximum Likelihood; Pre-test; Random coefficient regression;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
- C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
This paper has been announced in the following NEP Reports:
- NEP-ALL-2003-08-31 (All new papers)
- NEP-ECM-2003-08-31 (Econometrics)
- NEP-ETS-2003-08-31 (Econometric Time Series)
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