The following is a summary of “Methodologic Issues Specific to Prediction Model Development and Evaluation,” published in the November 2023  issue of Pulmonology by Jin et al.

A broad number of mistakes have the potential to occur throughout the process of creating and testing statistical prediction models, which is a challenging endeavor in and of itself. These errors may occur in a variety of different ways. A wide range of possible types of faults might occur here. For a study, researchers sought to present an overview of what they regard to be some of the most notable methodological hurdles that there was a chance of facing on occasion. 

These obstacles are potential challenges. The viewpoints that are offered here are taken from the personal experiences that the authors have directly experienced. Additionally, to provide a more comprehensive explanation, they described each problem and provided some advice on how to deal with them. 

It was done to provide a more comprehensive explanation. To offer a more in-depth explanation, this was done to fulfill the requirements. They sought to accomplish the target of this piece, which is to bring about the release of statistical prediction models that are of a higher quality. It was anticipated that publishing this paper would bring about the successful accomplishment of the objective.

Source: sciencedirect.com/science/article/abs/pii/S0012369223009455