Modelo de regresión beta con valores daltantes en las covariables: Una aplicación sobre la tasa de pobreza multidimensional de los municipios de Colombia.

Abstract

In many studies modeling variables of interest, it is common to encounter missing data for the explanatory variables. This presents a challenge in terms of how to properly handle this data, as the very nature of the variables influences the strategies that should be implemented. In this regard, one of the most frequently used strategies for handling missing data is imputation. While there are various ways to apply this process, it is not always done correctly, since in some cases the fact that the chosen statistical method and imputation method are closely linked is not taken into account. Therefore, a methodology was developed for handling missing values ​​in explanatory variables within a beta regression model, allowing the modeling of proportion or ratio variables, such as the poverty rate. This is a topic of great interest for public policy formulation, especially for generating actions and projects focused on improving the quality of life for people in the country.