Regression Modeling Strategies: With Applicatio... | TRUSTED - BREAKDOWN |
š If you want to stop just "running regressions" and start building robust, honest models, this is the most important book you will ever read.
Heavy emphasis on multiple imputation rather than deleting rows. Regression Modeling Strategies: With Applicatio...
Extensive use of restricted cubic splines to let the data dictate the shape of relationships. š If you want to stop just "running
A rigorous focus on bootstrapping for internal validation rather than simple data-splitting. A rigorous focus on bootstrapping for internal validation
Harrellās primary mission is to combat . He argues against common but flawed practices like: Using P-values to select variables (Stepwise regression). Dropping "insignificant" variables from a final model.
It is dense. It assumes a solid foundation in statistics and familiarity with R (specifically the rms package).
Provides clear rules of thumb (like the 15-to-1 ratio) for how many variables a dataset can actually support. āļø The Verdict
