The article introduces a new way to decide whether to use a simple or complex model for data analysis. By using a measure called the parametricness index (PI), researchers can determine if a chosen model is accurate enough for the data. This helps in selecting the best method for estimating the relationship between variables. The study shows that by switching between different criteria based on the PI, the resulting estimates are more accurate for both simple and complex situations. The PI was tested on simulated and real data, proving its usefulness in practical applications.