General score tests for regression models incorporating 'robust' variance estimates

Stata incorporates commands for carrying out two of the three general approaches to asymptotic significance testing in regression models, namely likelihood ratio (lrtest) and Wald tests (testparms). However, the third approach, using "score" tests, has no such general implementation. This omission is particularly serious when dealing with "clustered" data using the Huber-White approach. Here the likelihood ratio test is lost, leaving only the Wald test. This has relatively poor asymptotic properties. Our paper describes a general implementation of score tests which generalizes to the clustered data case.