Replication Data for: Extending the Use and Prediction Precision of Subnational Public Opinion Estimation
<|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:'The comparative study of subnational units is on the rise. Multilevel regression and post-stratification (MrP) has become the standard method for estimating subnational public opinion. Unfortunately, MrP comes with stringent data demands. As a consequence, scholars cannot apply MrP in countries without detailed census data, and when such data is available, the modeling is restricted to a few variables. This article introduces multilevel regression with synthetic post-stratification (MrsP), which relaxes the data requirement of MrP to marginal distributions, substantially increases the prediction precision of the method, and extends its use to countries without census data. The findings of Monte Carlo, U.S., and Swiss analyses show that, using the same predictors, MrsP usually performs in standard applications as well as the currently use' . 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" : ["Small area estimation","Subnational government","Surveys"]} <|eot_id|>
 Here is the Description of a dataset. Description:'The comparative study of subnational units is on the rise. Multilevel regression and post-stratification (MrP) has become the standard method for estimating subnational public opinion. Unfortunately, MrP comes with stringent data demands. As a consequence, scholars cannot apply MrP in countries without detailed census data, and when such data is available, the modeling is restricted to a few variables. This article introduces multilevel regression with synthetic post-stratification (MrsP), which relaxes the data requirement of MrP to marginal distributions, substantially increases the prediction precision of the method, and extends its use to countries without census data. The findings of Monte Carlo, U.S., and Swiss analyses show that, using the same predictors, MrsP usually performs in standard applications as well as the currently use' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
The comparative study of subnational units is on the rise. Multilevel regression and post-stratification (MrP) has become the standard method for estimating subnational public opinion. Unfortunately, MrP comes with stringent data demands. As a consequence, scholars cannot apply MrP in countries without detailed census data, and when such data is available, the modeling is restricted to a few variables. This article introduces multilevel regression with synthetic post-stratification (MrsP), which relaxes the data requirement of MrP to marginal distributions, substantially increases the prediction precision of the method, and extends its use to countries without census data. The findings of Monte Carlo, U.S., and Swiss analyses show that, using the same predictors, MrsP usually performs in standard applications as well as the currently use
Small area estimation; Subnational government; Surveys