I have developed a survey that includes a Choice-Based Conjoint (CBC) experiment with approximately 2,000 participants. The survey is divided into several groups. Group 1 serves as the reference group (receiving no treatment), while Groups 2-5 consist of different treatment groups (some receiving visual treatments, others textual interventions). My objective is to determine whether each treatment group significantly differs from the reference group. I am considering using covariates and Hierarchical Bayes (HB) Analysis for this purpose. However, I am unsure about how to interpret the results in this context. Additionally, I am contemplating whether to divide the sample into multiple smaller subsets (e.g., reference + treatment 1, reference + treatment 2, etc.) for analysis with covariates, or if there is a more straightforward approach available. Thank you!