The article explores how to make accurate estimations when dealing with unknown factors in scientific studies. By using a method called integrated likelihood, researchers can remove these unknown factors and focus on the main parameter of interest. The study shows that by carefully choosing the prior density, the integrated likelihood function can be a valuable tool for making reliable estimations without needing to be a Bayesian expert.