REGRESSION MODELING STRATEGIES 2ND ED.
Ouvrage 9780387952321 : REGRESSION MODELING STRATEGIES 2ND ED.
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 "too many
variables to analyze and not enough observations," and powerful model
validation techniques based on the bootstrap. This text realistically
deals with model uncertainty and its effects on inference to achieve
"safe data mining".
Contents: General Aspects of Fitting Regression Models.- Missing Data.-
Multivariate Modeling Strategies.- Resampling, Validating, Describing,
and Simplifying the Model.- S-PLUS Software.- Case Study in Least
Squares Fitting and Interpretation of a Linear Model.- Case Study in
Imputation and Data Reduction.- Overview of Maximum Likelihood
Estimation.- Binary Logistic Regression.- Logistic Model Case Study 1:
Predicting Cause of Death.- Logistic Model Case Study 2: Survival of
Titanic Passengers.- Ordinal Logistic Regression.- Case Study in Ordinal
Regression, Data Reduction, and Penalization.- Models Using Nonparametic
Transformations of X and Y.- Introduction to Survival Analysis.-
Parametric Survival Models.- Case Study in Parametric Survival Modeling
and Model Approximation.- Cox Proportional Hazards Regression Model.-
Case Study in Cox Regression.
Auteur : HARRELL
Editeur : TELOS
Nombre de pages : 568
Date de publication : 01 2001
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