The article discusses different ways to analyze data with multiple categories using a type of mathematical model called functional logit models. These models help predict outcomes based on patterns in the data. The researchers used a method called functional principal component analysis to estimate the relationships between variables. They found that by using this approach, they could accurately reconstruct the true patterns in the data even when the observations were not evenly spaced.