1. The coefficients can be discussed in terms of either Z-scores or probit index;
2. Describing the results in terms of Z-scores may not be the simplest metric for your audience to understand.  As we saw above, you can use the prvalue, prtab and other spost commands to obtain predicted probabilities.  These are often useful for helping to tell the "story" of your results.
3. that although it is possible to interpret the probit coefficients as changes in z-scores we end up convert the z-scores to probabilities. So, in the end its probably better to focus on the probabilities and/or the changes in probability in interpreting your probit model.
4. probit coefficient, b, is that a one-unit increase in the predictor leads to increasing the probit score by b standard deviations.

[此贴子已经被作者于2008-6-14 5:09:23编辑过]

看看计量的书上讲了

green的书/woodridge的都有啊