Post-Stratification without Population Level Information on the Post-Stratifying Variable, with Application to Political Polling
- Creators
- Reilly, Cavan
- Gelman, Andrew
-
Katz, Jonathan N.
Abstract
We investigate the construction of more precise estimates of a collection of population means using information about a related variable in the context of repeated sample surveys. The method is illustrated using poll results concerning presidential approval rating (our related variable is political party identification). We use post-stratification to construct these improved estimates, but since we don't have population level information on the post-stratifying variable, we construct a model for the manner in which the post-stratifier develops over time. In this manner, we obtain more precise estimates without making possibly untenable assumptions about the dynamics of our variable of interest, the presidential approval rating.
Additional Information
C. Reilly and A. Gelman thank the NSF for grant SBR-9708424 and Young Investigator Award DMS-9796129, and J. Katz thanks the John M. Olin Foundation. Published as Reilly, C., Gelman, A., & Katz, J. (2001). Poststratification without population level information on the poststratifying variable with application to political polling. Journal of the American Statistical Association, 96(453), 1-11.Attached Files
Submitted - sswp1091.pdf
Files
Name | Size | Download all |
---|---|---|
md5:d7cc855cba9f7238cc275b184e3d7257
|
300.9 kB | Preview Download |
Additional details
- Eprint ID
- 79957
- Resolver ID
- CaltechAUTHORS:20170808-143149807
- NSF
- SBR-9708424
- NSF
- DMS-9796129
- John M. Olin Foundation
- Created
-
2017-08-09Created from EPrint's datestamp field
- Updated
-
2020-11-19Created from EPrint's last_modified field
- Caltech groups
- Social Science Working Papers
- Series Name
- Social Science Working Paper
- Series Volume or Issue Number
- 1091