LOGISTIC REGRESSION MODELLING WITH VARIABLE SELECTION AND BEST MODEL EVALUATION IN THE ANALYSIS OF VARIABLES INFLUENCING TODDLER NUTRITIONAL STATUS - Pujianto, Tutut; Santoso, Puguh; Anggraeni, Enggar (Jurnal Wiyata Penelitian Sains dan Kesehatan, 2025)
Background: Nutritional status is one of the measures used to evaluate the adequacy of nutrition in toddlers. Many factors can affect the nutritional status of toddlers, including breastfeeding, infectious diseases, and the clean water facilities used. Considering the importance of the toddler period, high-quality analysis is needed to produce accurate outputs. One analysis that can be used to predict the role of causal factors on the resulting outcomes is ordinal logistic regression analysis, which can be obtained from logit and probit models. Objective: To determine whether a logit or probit model will be used in the analysis, simulation in its application needs to be carried out.. Method: This research uses baseline data from Pelem Village, Pare District, Kediri Regency in 2023. The selection of the best model is based on the model fitting parameter values, goodness of fit, and pseudo R square. Result : From the simulation results, it was found that the logit model produces a better model than the probit model. Furthermore, with ordinal regression analysis using the logit model, no relationship model was formed because all independent variables had p-values greater than 0.05. Conclusions: The absence of a model indicates that there is no effect of breastfeeding, infectious diseases, and clean water facilities on the nutritional status of toddlers.