The selection of the most important factors affecting the infected with cholera using generalized Bayesian lasso regression

• Post by: Muthanna mjdes
• أكتوبر 9, 2024
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Abstract

Regression analysis is considered an important statistical tool in analyzing data that requires finding a statistical method it studies the relationship between the response variable and a group of explanatory variables, as it helps in estimating the regression equation to understand the relationship between variables, in addition to preparing statistical models, including the multiple linear regression model It is an essential tool for researchers in all fields, including the health field, to clarify the risks resulting from some diseases Detecting it helps prevent the development of the disease and treat the disease early through the necessary medical care To prevent deterioration of the condition. The successful researcher must choose the correct model and interpret the results accurately. The Lasso regression model is one of the most important statistical topics for selecting explanatory variables by organizing and reducing important variables Also, choosing the wrong regression model to analyze and estimate the data will result in inconsistent estimates of the parameters of the model under study Which leads to unhelpful estimates, and therefore the explanatory variables included in the regression model do not explain the variables occurring in a clear and correct way. Therefore, Bayesian generalized Lasso regression it was used to obtain consistent and unbiased estimates and choose the most important explanatory variables that affect cholera disease. The issue of selecting variables in medical cases helps to determine the most important factors affecting the incidence of the disease, as well as ease of communication between the doctor and patients

مجلة المثنى للعلوم الادارية والاقتصادية, 2024,المجلد 1, العدد 1, الصفحات 297-301

DOI:10.52113/6/2024-S-1/297-301