Generalized linear mixed models for small area estimation

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F19%3A00335961" target="_blank" >RIV/68407700:21340/19:00335961 - isvavai.cz</a>
Result on the web
<a href="http://gams.fjfi.cvut.cz/spms2019" target="_blank" >http://gams.fjfi.cvut.cz/spms2019</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Generalized linear mixed models for small area estimation
Original language description
Small area estimation is a field of statistics which deals with the problem of obtaining reliable estimates of characteristics of interest in situations when the sample is divided into domains for which the sample sizes are often small. For the use in this field a new unit-level logit mixed model is proposed. The model uses fixed effects for areas with larger sample sizes and models the rest of the domains by random effects. In order to predict area means empirical best predictor and plug-in predictor are used and compared via a simulation experiment. Simulation studies are carried out in order to compare the quality of predictions acquired from the proposed model with predictions obtained from a binomial logit-mixed model which only uses random effects to model the domains. The two models are applied to the estimation of poverty risks in counties of the region of Valencia, Spain, and their predictions are compared.
Czech name
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Czech description
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Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of SPMS 2019 - Stochastic and Physical Monitoring Systems
ISBN
978-80-01-06659-1
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
57-64
Publisher name
Česká technika - nakladatelství ČVUT
Place of publication
Praha
Event location
Dobřichovice
Event date
Jun 20, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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