Why can’t we use regular (OLS) Regression?

Fundamentals of Social Statistics by Adam J. McKee

Applying OLS regression to dichotomous dependent variables is problematic for several reasons.  A major reason is that it violates some important assumptions:  The errors cannot be normally distributed, and they cannot have a constant variance.  In addition, such a linear model does not confine the level of the variable to a valid, discrete category.  That is, predicted values based on such a model would fall outside of the logical range of zero and one.

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Last Modified:  02/14/2019


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