knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
The ACS is the main dataset used for post-stratification in MRP because of its wide coverage of different geographies. However, there are a couple of data limitations to the ACS that make subsequent MRP diverge from the classic MRP as it is usually taught:
vignette("synth", package = "synthjoint")
) in this package to see how this restriction could be relaxed.This package and vignette goes into more detail about these limitations and the nature of the data that is available.
If you are in a hurry or want something to start with, here are three partitions this package provides:
?acscodes_age_sex_educ
.?acscodes_age_sex_race
.?acscodes_sex_educ_race
See their help pages for more information and their limitations.
The survey and the post-stratification must share discrete variables the level of which match 1:1. Therefore, if race is binned 9 ways in the ACS but there are only 5 response options in the CCES, then the finer group must be collapsed to coarser groupings of the 5 levels in the CCES. That also means, for example, that the recoding must be nested -- i.e., it is hard to salvage two variable codings that are not many-to-one nested mappings to each other. These judgments must be made with careful attention to the question wording and are documented to some extent in ?namevalue
.
The statements in this vignette benefited from many online resources and correspondence with experts including Yair Ghitza and Matto Mildenberger. I also relies on findings from several published papers:
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