Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis, 2nd Edition
Regression Modeling Strategies: With Applications to Linear Models, Logistic and Ordinal Regression, and Survival Analysis, 2nd Edition
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DOI：
10.1007/978-3-319-19425-7
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发表时间：
2015-01-01
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影响因子：
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通讯作者：
Harrell, F. E.
中科院分区：
文献类型：
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作者：
Harrell, F. E.
许多课本是关于单个统计工具的极好的知识来源，但数据分析的艺术是关于选择和使用多种工具的。而不是提出孤立的技术，这篇文章强调的问题解决策略，解决了许多问题时，发展多变量模型使用真实的数据，而不是标准的教科书例子。它包括有效处理缺失数据的补偿方法、处理非线性关系和使转换估计成为建模过程的正式部分的方法、处理“要分析的变量太多且观测不足”的方法，以及基于Bootstrap的强大的模型验证技术。本文实事求是地处理模型不确定性及其对推理的影响，以实现“安全数据挖掘”。
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".