Target estimation and adjustment weighting for survey nonresponse and sampling bias:
We elaborate a general workflow of weighting-based survey inference, decomposing it into two main tasks. The first is the estimation of population targets from one or more sources of auxiliary information. The second is the construction of weights that calibrate the survey sample to the population t...
Gespeichert in:
| Hauptverfasser: | , , , , , |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2020
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| Schlagworte: | |
| Online-Zugang: | BSB01 UBG01 Volltext |
| Zusammenfassung: | We elaborate a general workflow of weighting-based survey inference, decomposing it into two main tasks. The first is the estimation of population targets from one or more sources of auxiliary information. The second is the construction of weights that calibrate the survey sample to the population targets. We emphasize that these tasks are predicated on models of the measurement, sampling, and nonresponse process whose assumptions cannot be fully tested. After describing this workflow in abstract terms, we then describe in detail how it can be applied to the analysis of historical and contemporary opinion polls. We also discuss extensions of the basic workflow, particularly inference for causal quantities and multilevel regression and poststratification |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 07 Oct 2020) |
| Beschreibung: | 1 Online-Ressource (87 Seiten) |
| ISBN: | 9781108879217 |
| DOI: | 10.1017/9781108879217 |
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| 520 | |a We elaborate a general workflow of weighting-based survey inference, decomposing it into two main tasks. The first is the estimation of population targets from one or more sources of auxiliary information. The second is the construction of weights that calibrate the survey sample to the population targets. We emphasize that these tasks are predicated on models of the measurement, sampling, and nonresponse process whose assumptions cannot be fully tested. After describing this workflow in abstract terms, we then describe in detail how it can be applied to the analysis of historical and contemporary opinion polls. We also discuss extensions of the basic workflow, particularly inference for causal quantities and multilevel regression and poststratification | ||
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| spelling | Caughey, Devin ca. 20./21. Jh. (DE-588)1161755470 aut Target estimation and adjustment weighting for survey nonresponse and sampling bias Devin Caughey, Adam J. Berinsky, Sara Chatfield, Erin Hartman, Eric Schickler, Jasjeet S. Sekhon Target Estimation & Adjustment Weighting for Survey Nonresponse & Sampling Bias Cambridge Cambridge University Press 2020 1 Online-Ressource (87 Seiten) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 07 Oct 2020) We elaborate a general workflow of weighting-based survey inference, decomposing it into two main tasks. The first is the estimation of population targets from one or more sources of auxiliary information. The second is the construction of weights that calibrate the survey sample to the population targets. We emphasize that these tasks are predicated on models of the measurement, sampling, and nonresponse process whose assumptions cannot be fully tested. After describing this workflow in abstract terms, we then describe in detail how it can be applied to the analysis of historical and contemporary opinion polls. We also discuss extensions of the basic workflow, particularly inference for causal quantities and multilevel regression and poststratification Sampling (Statistics) Inference Estimation theory (DE-588)4143413-4 Aufsatzsammlung gnd-content Berinsky, Adam J. 1970- (DE-588)139564985 aut Chatfield, Sara ca. 20./21. Jh. (DE-588)122031305X aut Hartman, Erin ca. 20./21. Jh. (DE-588)1220313556 aut Schickler, Eric 1969- (DE-588)135933757 aut Sekhon, Jasjeet Singh 1971- (DE-588)122031420X aut Erscheint auch als Druck-Ausgabe 978-1-108-79415-2 https://doi.org/10.1017/9781108879217 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Caughey, Devin ca. 20./21. Jh Berinsky, Adam J. 1970- Chatfield, Sara ca. 20./21. Jh Hartman, Erin ca. 20./21. Jh Schickler, Eric 1969- Sekhon, Jasjeet Singh 1971- Target estimation and adjustment weighting for survey nonresponse and sampling bias Sampling (Statistics) Inference Estimation theory |
| subject_GND | (DE-588)4143413-4 |
| title | Target estimation and adjustment weighting for survey nonresponse and sampling bias |
| title_alt | Target Estimation & Adjustment Weighting for Survey Nonresponse & Sampling Bias |
| title_auth | Target estimation and adjustment weighting for survey nonresponse and sampling bias |
| title_exact_search | Target estimation and adjustment weighting for survey nonresponse and sampling bias |
| title_exact_search_txtP | Target estimation and adjustment weighting for survey nonresponse and sampling bias |
| title_full | Target estimation and adjustment weighting for survey nonresponse and sampling bias Devin Caughey, Adam J. Berinsky, Sara Chatfield, Erin Hartman, Eric Schickler, Jasjeet S. Sekhon |
| title_fullStr | Target estimation and adjustment weighting for survey nonresponse and sampling bias Devin Caughey, Adam J. Berinsky, Sara Chatfield, Erin Hartman, Eric Schickler, Jasjeet S. Sekhon |
| title_full_unstemmed | Target estimation and adjustment weighting for survey nonresponse and sampling bias Devin Caughey, Adam J. Berinsky, Sara Chatfield, Erin Hartman, Eric Schickler, Jasjeet S. Sekhon |
| title_short | Target estimation and adjustment weighting for survey nonresponse and sampling bias |
| title_sort | target estimation and adjustment weighting for survey nonresponse and sampling bias |
| topic | Sampling (Statistics) Inference Estimation theory |
| topic_facet | Sampling (Statistics) Inference Estimation theory Aufsatzsammlung |
| url | https://doi.org/10.1017/9781108879217 |
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