1,853,185 research outputs found
Multipurpose small area estimation
Sample surveys are generally multivariate, in the sense that they measure more than oneresponse variable. In theory, each variable can then be assigned an optimal weight forestimation purposes. However, it is often a distinct practical advantage to have a singleweight that is used with all variables collected in the survey. This paper describes howsuch multipurpose sample weights can be constructed when small area estimates of thesurvey variables are required. The approach is based on the model-based direct (MBD)method of small area estimation described in Chambers and Chandra (2006). Empiricalresults reported in this paper show that MBD estimators for small areas based onmultipurpose weights perform well across a range of variables that are often of interest inbusiness surveys. Furthermore, these results show that the proposed approach is robust tomodel misspecification and also efficient for the variables ill-suited to standard methodsof small area estimation (e.g. variables that contain a significant proportion of zeros).<br/
Unchained Poem by Lee Chambers
Text document the poem Unchained by Lee Chambers, Jr. published in the November 1973 issue of the New Era Magazine a publication of the LDS Churchconverted from .jpg to .pdf for compatibilit
Emails between Connell O\u27Donovan and Lee Chambers on BYU Homosexual Crackdown
Text Document Personal Emails sent between Lee Chambers and Connell O\u27Donovan Same document as Lee Chambers Emails - 2004.docxconverted from .docx to .pdf for compatibili
Calibrated Weighting for Small Area Estimation
Calibrated weighting methods for estimation of survey population characteristics are widely used. At the same time, model-based prediction methods for estimation of small area or domain characteristics are becoming increasingly popular. This paper explores weighting methods based on the mixed models that underpin small area estimates to see whether they can deliver equivalent small area estimation performance when compared with standard prediction methods and superior population level estimation performance when compared with standard calibrated weighting methods. A simple MSE estimator for weighted small area estimation is also developed
Improved Direct Estimators for Small Areas
Unbiased direct estimators for small area quantities are usually considered too variable to be of any practical use. In this paper we propose a class of model-based direct estimators for small area quantities that appears to overcome this objection, in the sense that these estimators are comparable in efficiency to the indirect model-based small area estimators (e.g. empirical best linear unbiased predictors, or EBLUPs) that are now widely used. There are many practical advantages associated with such model-based direct (MBD) estimators, arising from the fact that they are computed as weighted linear combinations of the actual sample data from the small areas of interest. Note that in this case the weights ‘borrow strength’ via a model that explicitly allows for small area effects. One particular advantage that we explore in this paper is that estimation of mean squared error (MSE) is then straightforward, using well-known methods that are in common use for population level estimates. Empirical results reported in this paper show that the MBD estimator represents a real alternative to the EBLUP, with the simple MSE estimator associated with the MBD estimator providing good coverage performance. We also report results that indicate that the MBD estimator may be more robust than the EBLUP when the small area model is incorrectly specified. Furthermore, the MBD approach is easily extended to provide multi-purpose weights that are efficient across a range of variables, including variables that are unsuitable for EBLUP, e.g. variables that contain a significant proportion of zeros
[Report to Chief J. E. Curry by W. E. Chambers, regarding the murder of Lee Harvey Oswald #4]
Report to Chief J. E. Curry by W. E. Chambers regarding officer's assignment and the murder of Lee Harvey Oswald. Chambers describes his duties, actions, and observations as a security guard during the transfer of Oswald to the County Jail
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