The effect of a binary predictor is to shift the regression intercept.

Question

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A binary predictor can be thought of as a variable that takes on only two values (e.g. 0 or 1). When included in a regression model, the effect of the binary predictor is to add a fixed amount to the intercept for one group and subtract the same amount from the intercept for the other group. This shift in intercept can be interpreted as a change in the baseline level of the outcome variable for the two groups defined by the binary predictor.

The Effect of a Binary Predictor Is to Shift the Regression