The Likelihood Ratio Test (LRT) is a statistical method used to compare the goodness of fit between two models. It evaluates how well each model explains the observed data by calculating the ratio of their likelihoods. A higher ratio indicates that one model fits the data significantly better than the other, helping researchers decide which model is more appropriate. In practice, the LRT is often used in fields like biostatistics and econometrics to test hypotheses. It provides a formal way to assess whether adding parameters to a model improves its explanatory power, guiding decisions in model selection and validation.