For simplicity and speed and because of the large number of models estimated, the models were estimated using linear probability models, even when the dependent variable was binary. Logit and probit estimation techniques are generally recommended for estimating equations with zero-one dependent variables. However, the authors of the methodology reported that using logit or probit made it more difficult to interpret the results and created some complexities in calculating adjustments.

For example, they stated that because logit and probit are non-linear models, the adjustment factor could not be calculated using sample means but rather required calculating probabilities for all observations using the full set of data.

Further, the argument was made that econometricians had

shown that the drawbacks of using linear probability models, compared with logit and probit techniques, were minimal.

shown that the drawbacks of using linear probability models, compared with logit and probit techniques, were minimal.