A truncated regression model is like a regular regression model, but with some modifications. In a regular regression model, all the data is used to try to explain a certain outcome. In a truncated regression, some of the data points are left out, or "truncated". This means that the model does not take all of the data into account when trying to explain the outcome. It only takes into account part of the data, so it is more limited in what it can explain.