The article explores how to estimate data from a logistic model when some information is missing due to time constraints. Researchers looked at different methods to make these estimates more accurate. They found that the likelihood ratio method is more precise than the Wald and Rao methods, needing less data to get good results. The maximum likelihood estimator didn't always match the expected distribution, showing room for improvement in this area.