以下是一篇关于Logistic回归分析的英文文献的例子:
Title: "Logistic Regression: Why We Cannot Do What We Think We Can Do, and What We Can Do About It"
Author: Andrew Gelman, Jennifer Hill
Journal: European Sociological Review
Year: 2007
Abstract: Logistic regression is a widely used statistical technique for modeling binary outcomes. However, there are several common misconceptions about its interpretation and the assumptions underlying the model. In this article, Gelman and Hill discuss these misconceptions and propose alternative approaches to address them. They argue that logistic regression should not be used as a tool for causal inference, but rather as a descriptive tool for exploring associations between variables. The authors also highlight the importance of considering interactions and non-linear relationships when using logistic regression. They provide concrete examples and recommendations for improving the practice of logistic regression analysis.
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