Hybrid calibration methods for small domain estimation
|
digital
Articolo
|
||||||||||||||||||||
Articolo |
Ebook in formato Pdf leggibile su questi device:
|
|
|
|
|
Hybrid calibration refers to an approach where techniques of classical calibration and more recent model-assisted calibration are combined for a joint calibration methodology. The classical calibration does not assume a model but uses the original auxiliary data as aggregates, whereas in model calibration, unit-level predictions from a model are used as pseudo auxiliary information. By combining these approaches we introduce hybrid methods, where aggregate data from different levels of the population are supplied to the model-free component and unit-level data are incorporated into the model-assisted component. The choice of the model depends on the type of the target variable. We use here linear and logistic mixed models. In the estimation for population subgroups or domains, the classical calibration fails when domain sample sizes become small. Our hybrid calibration methods were more accurate in small domains. In our studies, the basic model-assisted calibration was usually the best in accuracy, but the method requires population-level information on auxiliary variables in the model. The basic hybrid calibration method overcomes this restriction by including a model-free calibration component in the model-assisted calibration procedure. A new two-level hybrid calibration technique provides a further extension applicable for hierarchically structured populations. In this method, calibration in the model-free part is performed at a higher regional level, instead of the domain level. In our simulation experiments, the two-level hybrid calibration performed well: its accuracy and design bias were comparable to model calibration. The most stable weight distributions were obtained by the two-level method and Ha´jek type estimators developed in the paper.
keywordsAuxiliary Information, Model-assisted Calibration, Mixed Models, Survey Weights, Design- based Simulation Experiments.Biografia degli autoriDepartment of Statistics - University of Helsinki (e-mail: risto.lehtonen@helsinki.fi; ari.veijanen@gmail.com). |
News
02.05.2022
I nostri eventi al Salone del Libro 2022
Dal 19 al 23 maggio saremo al Salone Internazionale del libro di Torino: vi aspettiamo al Pad. 2 stand L69 per tanti eventi e grandi ospiti.
09.05.2022
Mafia: fare memoria per combatterla
Il 13 maggio Antonio Balsamo presenta "Mafia. Fare memoria per combatterla" a Palermo, con Rosario Aitala, Caterina Chinnici e Maria Falcone.
28.04.2022
I libri dedicati ad Armida Barelli
Le iniziative editoriali dedicate alla Sorella Maggiore, per ricostruirne il pensiero e la vita in occasione della beatificazione del 30 aprile.
11.04.2022
L'icona, finestra dell'Oltre
Intervista a Giuliano Zanchi, autore di "Icone dell'esilio. Immagini vive nell'epoca dell'Arte e della Ragione".
Archivio rivista
In evidenza
