I have a Poisson model which I use on a medical data set with 329 observations. In the regression I am particularly interested in the simple Wald statistic for a single coefficient:
$$t = \frac{\widehat{\beta} – \beta}{s.e.(\widehat{\beta})}$$
I was told that simply using the robust option will not help and it was suggested that I use the percentile t-method for conducting the Wald test to refine the t-statistic. I know that I have to use the bootstrap command in Stata but I have not figured it out completely. The theoretical points about this type of refinement are clear but the problem is to implement it and then to know what the resulting $t$ tells me compared to the un-refined one. Any guidance on this would be much appreciated.
Solved – Robust Wald test for Poisson with Stata
bootstraphypothesis testingstatat-test
Best Answer
As far as I know there is no ready made command for your purpose in Stata but it does not seem to be necessary because it can be easily implemented by hand. If you run your regression
Create a local which holds the coefficient of your variable of interest (call it "bx", for instance) and then use the bootstrap command on the test statistic you posted.
If you need your results to be replicable, set a seed first. Once you have the result you can compare the bootstrapped standard error of "twald" with the standard deviation of the standard normal which is 1 (if this is what you meant by comparing the refined t with the un-refined t).