Linear regression and the normality assumption

Researchers often perform arbitrary outcome transformations to fulfill the normality assumption of a linear regression model. This commentary explains and illustrates that in large data settings, such transformations are often unnecessary, and worse may bias model estimates.

Source: Journal of Clinical Epidemiology - December 16, 2017 Category: Epidemiology Authors: Amand F. Schmidt, Chris Finan Tags: Commentary Source Type: research