Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for dealing with nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with qtoo many variables to analyze and not enough observations, q and powerful model validation techniques based on the bootstrap. This text realistically deals with model uncertainty and its effects on inference to achieve qsafe data miningq.Exercise treadmill score for predicting prognosis in coronary ... S-PLUS 2000 Guide to Statistics, Volume 1. MathSoft Data Analysis Products Division, Seattle, WA, 1999. [378 MathSoft. S-PLUS 2000 Usera#39;s Guide. Data Analysis Productsanbsp;...
|Title||:||Regression Modeling Strategies|
|Author||:||Frank E. Harrell|
|Publisher||:||Springer Science & Business Media - 2013-03-09|