Post-Stratification: A Modeler's Perspective
By Roderick J. A. Little. 1993
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Jake M. Hofman
- Amit Sharma
- John Robert Warren
- Andrew Halpern-Manners
- Duncan J. Watts
- Matthew S. Crow
- Jamie A. Snyder
- Vaughn J. Crichlow
Citations in the corpus
- Community Perceptions of Police Body-Worn Cameras (2017, background): “Poststratification mitigates the potential bias caused by a nonrepresentative sample (Hahs-Vaughn & Lomax, 2006; Little, 1993; Loosveldt & Sonck, 2008).”
- Panel Conditioning in Longitudinal Social Science Surveys (2012, methodology): “These weights can, in turn, be used to correct for known discrepancies between a sample and a target population, which arise as a result of nonresponse or related coverage issues (see, e.g., Little 1993).”
- Estimating the Causal Impact of Recommendation Systems from Observational Data (2015, result): “…one can deal with issues of representativeness (which can also arise when trying to generalize the results of randomized experiments) via post-stratification to reweight our causal click-through estimates so that they mirror those of a randomly drawn sample of product visits [Little 1993].”
- Does Weighting for Nonresponse Increase the Variance of Survey Means (2004, unknown): “This finding replicates previous results on post-stratification (Holt and Smith 1979; Little 1993).”
- Model Averaging Methods for Weight Trimming (2008, unknown): “…and thus (2.1) reduces toÐ pðYnobjYobs; uÞpðYobsjuÞpðuÞduÐ Ð pðYnobjYobs; uÞpðYobsjuÞpðuÞdudYnobs ¼ pðYnobjYobsÞ allowing inference about Q(Y) to be made without explicitly modeling the sampling inclusion parameter I (Ericson 1969; Holt and Smith 1979; Little 1993; Rubin 1987; Skinner et al. 1989).”
- Sampling weight adjustments in partial least squares structural equation modeling: guidelines and illustrations (2020, unknown): “Little, 1993).”
- Calibrated Bayes, an alternative inferential paradigm for official statistics (2012, background): “In the sample survey context, this issue arises in the question of whether the sampling distribution of post-stratified means should condition on post-stratum counts (Holt and Smith 1979; Little 1993).”