MRP, or to give it its full name, Multilevel Regression and Poststratification, is a form of advanced data science made popular by Professor Andrew Gelman. Professor Gelman first used it for election forecasts, while Latana is the first to use MRP for brand tracking. 

MRP creates a model and uses this model to generate estimates for responses in a survey. This model, when given a set of respondent characteristics, can produce an estimate for how that type of respondent would answer a survey question.

Following that, MRP organizes the respondent’s characteristics into groups. By doing so, they can better capture how the variables interact in real life.

Finally, MRP takes weighted averages of all the predictions. This is to ensure that the model has a fair sample of respondents.

Learn more about MRP here.

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