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Two Paradoxes in Linear Regression Analysis
Ge Feng1, Jing Peng2, Dongke Tu3
1School of Geophysics and Oil Resource, Yangtze University, Wuhan, China.
Abstract:
Regression is one of the favorite tools in applied statistics. However, misuse and misinterpretation of results from regression analysis are common in biomedical research. In this paper we use statistical theory and simulation studies to clarify some paradoxes around this popular statistical method. In particular, we show that a widely used model selection procedure employed in many publications in top medical journals is wrong. Formal procedures based on solid statistical theory should be used in model selection.
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