The article explores new ways to analyze data from different sources to understand how people make choices. By using two different models, the researchers show how to accurately estimate nested logit models with mixed preference data. They provide formulas to calculate utility function, dissimilarity, and scale parameter estimates. The study demonstrates how these methods can be applied to other models with multiple data sources, such as travel demand.