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What is Evaluating Regression Coefficients in GLMs about?

This document discusses the comparison between generalized linear models (GLMs) and traditional least-squares linear models (LMs) for analyzing non-Gaussian count data. It highlights that while GLMs may offer slight advantages in statistical power, they are prone to type I errors when mis-specified, whereas LMs provide robust tests across various conditions. The findings suggest that transforming data and applying LMs remains a valuable approach in ecological and evolutionary statistics.

Author

María Escobar

Language

EN