The value for the female by socst interaction is -.2047 which is the difference in slope between the male and female group, i.e., the slope for the female group would be about. 6247 which is the slope of the regression line for the male group (i.e., female=0). i.e., the expected value for write when both socst and female equal zero. This is the value of the intercept for socst regressed on write for males. LetвЂ™s interpret the coefficients for this model starting with the constant (17.76). Which tells us that the level for females is higher than for males. How could we tell that females are higher than males? The coefficient for female is positive (15.00) Looking at the graph, we can see that the two regression lines are not parallel and that the line for females falls above the line for males. (lfit write socst if ~female)(lfit write socst if female), /// Twoway (scatter write socst, msym(oh) jitter(3)) /// Please note that we use c.socst to indicate that socst is a continuous variable. We will begin by running the regression model and graphing the interaction. The continuous predictor variable, socst, is a standardized test score for social studies. The categorical variable is female, a zero/one variable with females coded as one (therefore, male is the reference group). We will use an example from the hsbdemo dataset that has a statistically significant categorical by continuous interaction to illustrate one possible explanatory approach. It means that the slope of the continuous variable is different for one or more levels of the categorical variable.

First off, letвЂ™s start with what a significant categorical by continuous interaction means.

Stata 12