Linear regression is a mathematical model that is employed broadly throughout all of social science research. The choice of parameterization for linear models has important substantive and statistical implications. This article examines the typical parameterization chosen, which includes a parameter for slope and a parameter for the y-intercept. The article demonstrates that the centercept has an interpretive advantage over the traditionally used y-intercept and that the centercept is typically estimated more accurately.
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