Data-Mining Homogeneous Subgroups in Multiple Regression When Heteroscedasticity, Multicollinearity, and Missing Variables Confound Predictor Effects (Q5066658)
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scientific article; zbMATH DE number 7500166
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Data-Mining Homogeneous Subgroups in Multiple Regression When Heteroscedasticity, Multicollinearity, and Missing Variables Confound Predictor Effects |
scientific article; zbMATH DE number 7500166 |
Statements
Data-Mining Homogeneous Subgroups in Multiple Regression When Heteroscedasticity, Multicollinearity, and Missing Variables Confound Predictor Effects (English)
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29 March 2022
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data mining
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multiple regression
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heteroscedasticity
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multicollinearity
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weighted least squares
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Monte Carlo
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