Testing The Equality Of Regression Coefficients And A Pooling Methodology From Multiple Samples When The Data Is Multicollinear
2009
- 17Usage
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
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- Usage17
- Downloads11
- Abstract Views6
Thesis / Dissertation Description
Testing the equality of regression coefficients between two regression equations is a common practice in statistics today. The theory and methods are sufficiently developed under ordinary least squares (OLS) estimation. However, there is no method for conducting such tests when OLS estimation is not an appropriate method. For example, when multicollinearity exists in the data.Therefore, there is a need for a method to test the equality of regression coefficients when the data is multicollinear. In this research, we will present methods for conducting such a test using ridge regression coefficient estimators and principal component estimators. We will also present a method for testing the equivalence of the OLS regression coefficients between two or more samples even in the presence of multicollinearity. Lastly, we will present a method for determining a ridge preliminary test estimator (PTE) and a PTE that incorporates the ridge and a stacked estimator.
Bibliographic Details
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