Replication data for: Deep Interactions with MRP: Election Turnout and Voting Patterns Among Small Electoral Subgroups
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'Using multilevel regression and poststratification (MRP), we estimate voter turnout and vote choice within deeply interacted subgroups: subsets of the population that are defined by multiple demographic and geographic characteristics. This article lays out the models and statistical procedures we use, along with the steps required to fit the model for the 2004 and 2008 Presidential elections. Though MRP is an increasingly popular method, we improve upon it in numerous ways: deeper levels of covariate interaction, allowing for non-linearity and non-monotonicity, accounting for unequal inclusion probabilities that are conveyed in survey weights, post-estimation adjustments to turnout and voting levels, and informative multidimensional graphical displays as a form of model checking. We use a series of examples to demonstrate the flexibilit' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Data visualization","Demographic variation","Geographic variation","Multilevel models","Multilevel regression and poststratification","Partisanship","Presidential elections","Public opinion","Statistical modeling","Stratification","Voter turnout"]} <|eot_id|>
 Here is the Description of a dataset. Description:'Using multilevel regression and poststratification (MRP), we estimate voter turnout and vote choice within deeply interacted subgroups: subsets of the population that are defined by multiple demographic and geographic characteristics. This article lays out the models and statistical procedures we use, along with the steps required to fit the model for the 2004 and 2008 Presidential elections. Though MRP is an increasingly popular method, we improve upon it in numerous ways: deeper levels of covariate interaction, allowing for non-linearity and non-monotonicity, accounting for unequal inclusion probabilities that are conveyed in survey weights, post-estimation adjustments to turnout and voting levels, and informative multidimensional graphical displays as a form of model checking. We use a series of examples to demonstrate the flexibilit' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
Using multilevel regression and poststratification (MRP), we estimate voter turnout and vote choice within deeply interacted subgroups: subsets of the population that are defined by multiple demographic and geographic characteristics. This article lays out the models and statistical procedures we use, along with the steps required to fit the model for the 2004 and 2008 Presidential elections. Though MRP is an increasingly popular method, we improve upon it in numerous ways: deeper levels of covariate interaction, allowing for non-linearity and non-monotonicity, accounting for unequal inclusion probabilities that are conveyed in survey weights, post-estimation adjustments to turnout and voting levels, and informative multidimensional graphical displays as a form of model checking. We use a series of examples to demonstrate the flexibilit
Data visualization; Demographic variation; Geographic variation; Multilevel models; Multilevel regression and poststratification; Partisanship; Presidential elections; Public opinion; Statistical modeling; Stratification; Voter turnout