The Rasch model is a statistical framework used in psychometrics to analyze responses to items in tests or questionnaires. It focuses on the relationship between individuals’ abilities and the difficulty of the items. The model assumes that the probability of a correct response to an item depends only on the person’s ability and the item’s difficulty. In this lecture Prof Jue Wang will explain Many Facets  Rasch Model (MFRM) which extends regular Rasch model by accommodating multiple sources of variation in this case is the involvement of rater/judge. The MFRM is capable for the examination of complex data structures, like multiple raters rating multiple items or individuals responding to items across different domains. By accounting for these facets simultaneously, the model provides a more comprehensive understanding of the underlying structure of the data, aiding in the development of more valid and reliable assessments. This also enhance understanding of data analysis to the individual level of rater, item as well as person, a manifestation of individualp-centered statistics.