Heavy emphasis on multiple imputation rather than deleting rows.
It is dense. It assumes a solid foundation in statistics and familiarity with R (specifically the rms package). Regression Modeling Strategies: With Applicatio...
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. Heavy emphasis on multiple imputation rather than deleting
Categorizing continuous predictors (e.g., splitting age into groups). 🛠️ Key Technical Strengths Regression Modeling Strategies: With Applicatio...
🚀 If you want to stop just "running regressions" and start building robust, honest models, this is the most important book you will ever read.
by Frank Harrell Jr. is widely considered the "gold standard" for applied statistical modeling. 🧠 The Core Philosophy