Abstract
The methods described in this book are useful in any regression model that involves a linear combination of regression parameters. The software that is described below is useful in the same situations. Functions in R 520 allow interaction spline functions as well as a wide variety of predictor parameterizations for any regression function, and facilitate model validation by resampling.
R is the most comprehensive tool for general regression models for the following reasons.
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Notes
- 1.
lrm and rcs are in the rms package.
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Harrell, F.E. (2015). R Software. In: Regression Modeling Strategies. Springer Series in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-19425-7_6
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