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- W2897969757 abstract "Abstract Researchers in political science often estimate linear models of continuous outcomes using least squares. While it is well known that least-squares estimates are sensitive to single, unusual data points, this knowledge has not led to careful practices when using least-squares estimators. Using statistical theory and Monte Carlo simulations, we highlight the importance of using more robust estimators along with variable transformations. We also discuss several approaches to detect, summarize, and communicate the influence of particular data points." @default.
- W2897969757 created "2018-10-26" @default.
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- W2897969757 date "2018-10-09" @default.
- W2897969757 modified "2023-10-16" @default.
- W2897969757 title "When BLUE is not best: non-normal errors and the linear model" @default.
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- W2897969757 doi "https://doi.org/10.1017/psrm.2018.34" @default.
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