Provides clear rules of thumb (like the 15-to-1 ratio) for how many variables a dataset can actually support. ⚖️ The Verdict
Extensive use of restricted cubic splines to let the data dictate the shape of relationships.
It is dense. It assumes a solid foundation in statistics and familiarity with R (specifically the rms package). Regression Modeling Strategies: With Applicatio...
A rigorous focus on bootstrapping for internal validation rather than simple data-splitting.
Categorizing continuous predictors (e.g., splitting age into groups). 🛠️ Key Technical Strengths Provides clear rules of thumb (like the 15-to-1
Harrell’s 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 bridges the gap between high-level theory and "boots-on-the-ground" data analysis. It teaches you how to build models that actually replicate in the real world. It assumes a solid foundation in statistics and
Heavy emphasis on multiple imputation rather than deleting rows.
Provides clear rules of thumb (like the 15-to-1 ratio) for how many variables a dataset can actually support. ⚖️ The Verdict
Extensive use of restricted cubic splines to let the data dictate the shape of relationships.
It is dense. It assumes a solid foundation in statistics and familiarity with R (specifically the rms package).
A rigorous focus on bootstrapping for internal validation rather than simple data-splitting.
Categorizing continuous predictors (e.g., splitting age into groups). 🛠️ Key Technical Strengths
Harrell’s 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 bridges the gap between high-level theory and "boots-on-the-ground" data analysis. It teaches you how to build models that actually replicate in the real world.
Heavy emphasis on multiple imputation rather than deleting rows.