- Tytuł:
- Estimation of mask effectiveness perception for small domains using multiple data sources
- Autorzy:
-
Sen, Aditi
Lahiri, Partha - Powiązania:
- https://bibliotekanauki.pl/articles/2028543.pdf
- Data publikacji:
- 2022-03-15
- Wydawca:
- Główny Urząd Statystyczny
- Tematy:
-
cross-validation
jackknife
survey data
synthetic estimation - Opis:
- Understanding the impacts of pandemics on public health and related societal issues at granular levels is of great interest. COVID-19 is affecting everyone in the globe and mask wearing is one of the few precautions against it. To quantify people's perception of mask effectiveness and to prevent the spread of COVID-19 for small areas, we use Understanding America Study's (UAS) survey data on COVID-19 as our primary data source. Our data analysis shows that direct survey-weighted estimates for small areas could be highly unreliable. In this paper, we develop a synthetic estimation method to estimate proportions of perceived mask effectiveness for small areas using a logistic model that combines information from multiple data sources. We select our working model using an extensive data analysis facilitated by a new variable selection criterion for survey data and benchmarking ratios. We suggest a jackknife method to estimate the variance of our estimator. From our data analysis, it is evident that our proposed synthetic method outperforms the direct survey-weighted estimator with respect to commonly used evaluation measures.
- Źródło:
-
Statistics in Transition new series; 2022, 23, 1; 1-20
1234-7655 - Pojawia się w:
- Statistics in Transition new series
- Dostawca treści:
- Biblioteka Nauki
Artykuł