Which of the following statements is NOT true regarding regression models for binary dependent variables?

The statement that logit and probit functions have negligible differences is not true. While both the logit and probit models are used for regression when the dependent variable is binary, they operate under different statistical assumptions and exhibit different mathematical characteristics.

The logit model uses the logistic function, which is derived from the logistic distribution, while the probit model is based on the cumulative distribution function of the standard normal distribution. These different underlying distributions lead to varying results in terms of coefficient interpretation and predicted probabilities, particularly at the extremes of the predicted probabilities.

It's worth noting that, although many practitioners may find that the results of logit and probit models are often similar in terms of predicted probabilities, they are not negligible; the choice between them can depend on the specific context or dataset being analyzed. Therefore, there are important distinctions between these two methods that make the assertion of negligible differences inaccurate.