Multilevel regression with poststratification
Multilevel Regression with Poststratification (MRP) is a statistical technique used for estimating preferences in sub-regions (e.g., states, individual constituencies) areas based on individual-level survey data gathered at other levels of aggregation (e.g., national surveys).[1]
The technique essentially involves using data from, for example, censuses relating to various types of people corresponding to different characteristics (e.g., age, race), in a first step to estimate the relationship between those types and individual preferences (i.e., multi-level regression of the dataset). This relationship is then used in a second step to estimate the sub-regional preference based on the number of people having each type/characteristic in that sub-region (a process known as "poststratification").[2] In this way the need to perform surveys at sub-regional level, which can be expensive and impractical in an area (e.g., a country) with many sub-regions (e.g. counties, ridings, or states), is avoided. It also avoids issues with consistency of survey when comparing different surveys performed in different areas.[3][1] Additionally, it allows the estimating of preference within a specific locality based on a survey taken across a wider area that includes relatively few people from the locality in question, or where the sample may be highly unrepresentative.[4]
History
The technique was originally developed by Gelman and Little in 1997. It was subsequently expanded on by Park, Gelman, and Bafumi in 2004 and 2006. It was proposed for use in estimating US-state-level voter preference by Lax and Philips in 2009. Warshaw and Rodden subsequently proposed it for use in estimating district-level public opinion in 2012.[1] Wang subsequently used it for estimating the outcome of the 2012 US presidential election based on a survey of X-Box users, and it has also been proposed for use in the field of epidemiology.[4]
The technique was used to successfully predict the 2016 election victory of Donald Trump.[5]
Limitations
MRP is considered relatively a relatively poor technique for estimating the change of opinion over time.[3]
References
- ^ a b c Buttice, Matthew K.; Highton, Benjamin (Autumn 2013). "How Does Multilevel Regression and Poststratification Perform with Conventional National Surveys?". Political Analysis. 21 (4): 449–451. Retrieved 31 October 2019.
- ^ "What is MRP?". Survation.com. Survation. Retrieved 31 October 2019.
- ^ a b Gelman, Andrew; Lax, Jeffrey; Phillips, Justin; Gabry, Jonah; Trangucci, Robert (28 August 2018). "Using Multilevel Regression and Poststratification to Estimate Dynamic Public Opinion" (PDF): 1–3. Retrieved 31 October 2019.
{{cite journal}}: Cite journal requires|journal=(help) - ^ a b Downes, Marnie; Gurrin, Lyle C.; English, Dallas R.; Pirkis, Jane; Currier, Diane; Spital, Matthew J.; Carlin, John B. (9 April 2018). "Multilevel Regression and Poststratification: A Modeling Approach to Estimating Population Quantities From Highly Selected Survey Samples". American Journal of Epidemiology. 179 (8): 187. Retrieved 31 October 2019.
- ^ Jones, Amy (30 OCTOBER 2019). "Lib Dems will stand aside for Dominic Grieve, as polling predicts a Boris Johnson majority". Daily Telegraph. Retrieved 31 October 2019.
{{cite news}}: Check date values in:|date=(help)