Logistic regression is widely used in complex data analysis. When predictors are at individual level and the response … at aggregate level, logistic regression can be estimated using the Maximum Likelihood Estimation (MLE) method with the …

, models were created for both predictive and explanatory purposes using the CHAID classification tree and logistic regression …

online from April to June 2023, with a sample size of 185 respondents. A logistic regression model was constructed using the …

state using eight binary logistic regression models. Findings - The main results of transitions from unemployment to … residents, and the results of the logistic regression models consistent with the transition probabilities matrix results, except …

inadequate or unfair; conversely, it increases if citizens perceive the government to be responding adequately. Logistic … regression results confirm this heterogeneity. Droughts, extreme temperatures, floods, and storms reduce tax morale, while …

, logistic regression-based models remain effective, especially when combined with class-balancing techniques. It is concluded …

and Sub-Saharan Africa regions using a binary logistic regression (BLR) model. The results indicated that educational …