Testing and Visualization of Associations in Three-Way Contingency Tables: A Study of the Gender Gap in Patients with Type 1 Diabetes and Cardiovascular Complications

Abstract

Using data from the Swedish National Diabetes Register, this study examines the gender disparity among patients with type 1 diabetes who have experienced a specific cardiovascular complication, while exploring the association between their weight variability, age group, and gender. Fourteen cardiovascular complications have been considered. This analysis is conducted using three-way correspondence analysis (CA), which allows for the partitioning and decomposition of Pearson’s three-way chi-squared statistic. The dataset comprises information organized in a data cube, detailing how weight variability among these patients correlates with a cardiovascular complication, age group, and gender. The three-way CA method presented in this paper allows one to assess the statistical significance of the association between these variables and to visualize this association, highlighting the gender gap among these patients. From this analysis, we find that the association between weight variability, age group, and gender varies among different types of cardiovascular complications.