Small Area Estimation
By J. Rao. 2003
896 citations recorded by the source corpus.
View Paper: https://www.semanticscholar.org/paper/2076f8a5fdad4a12463e8871664bedf17931a1c0
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- M. José Lombardía
- Miguel Boubeta
- Domingo Morales
- Jiming Jiang
- Partha Lahiri
- Angela Druckman
- Stefan Sperlich
- Tim Jackson
Citations in the corpus
- Smooth Transition from Fixed Effects to Mixed Effects Models in Multi-level regression Models (2008, background): “More recently they have also attracted a good amount of attention in small area statistics, see Ghosh and Rao (1994), Rao (2003), Jiang and Lahiri (2006) for reviews of small-area techniques.”
- Measuring resource inequalities: The concepts and methodology for an area-based Gini coefficient (2008, methodology): “This is an example of a " small area estimation " problem, in which direct data for a small area (known as a domain) are not available, and therefore national survey data are combined with an auxiliary data source to build a modelled relationship (Heady et al. 2003; Rao 2003).”
- Integration of forest mapping and inventory to support forest management (2010, background): “This problem is well-recognized in the statistical literature as small area estimation and can be handled only by using model-based approaches (e.g., Rao 2003).”
- ROBUST ESTIMATION OF SMALL‐AREA MEANS AND QUANTILES (2010, methodology): “…Journal of Statistics The standard approach to small-area estimation uses regression models to predict the small-area characteristics of interest, and incorporates random area effects to account for between-area variation beyond that explained by the model covariates (Fay & Herriot 1979, Rao 2003).”
- Nonparametric estimation of mean-squared prediction error in nested-error regression models (2005, unknown): “ference will be conducted conditionally on X, which denotes the set of explanatory data X ij for 1≤i≤n and 1≤j≤n i. The model (2.1) is a generalization of the unbalanced nested-error regression model [29, 31], and is commonly used to model two-level clustered data. For example, Battese, Harter and F”
- Guidelines for Analyzing Add Health Data (2006, methodology): “When the subpopulation option is used, only the cases defined by the subpopulation are included in the calculation of the estimate, but all cases are included in the calculation of the standard errors (see Cochran, 1977; Rao, 2003).”
- The Health of Lesbian, Gay, Bisexual, and Transgender People: Building a Foundation for Better Understanding (2011, unknown): “However, this method poses a variety of analytical challenges, and statistical methods for improving the estimation and analysis of small domains continue to be developed (Rao, 2003).”
- Patterns and causes of uncertainty in the American Community Survey (2014, background): “The second main cause of sampling error is heterogeneity in the population being measured (Rao 2003).”
- A measure of spatial stratified heterogeneity (2016, methodology): “If spatial stratified heterogeneity is trong, areal interpolation (Rao, 2003) and the sandwich method Wang et al., 2013) can perform the mapping.”
- Empirical best prediction under area-level Poisson mixed models (2016, background): “See the monograph Rao (2003) and the reviews of Ghosh and Rao (1994), Rao (1999), Pfeffermann (2002), Jiang and Lahiri (2006), Rao (2008) and Pfeffermann (2013) for an introduction to the SAE.”