0365252 20240103195631.520111031235959.9 000284884400002 10.1080/03610920903480858 13 s. www cav_un_epca*02525200361-0926405 (2011)785-797Taylor & Francis small area estimation Fay-Herriot model Linear mixed model Labor Force Survey cav_un_auth*0101108 Hobza Tomáš Stochastická informatika Department of Stochastic Informatics SI SI UTIA-B Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0015540 Morales D. ES cav_un_auth*0275007 Herrador M. ES cav_un_auth*0275008 Esteban M.D. ES http://library.utia.cas.cz/separaty/2011/SI/hobza-a%20fay-herriot%20model%20with%20different%20random%20effect%20variances.pdf 1M0572 GA MŠk cav_un_auth*0001814 CEZ:AV0Z10750506 A modification of the Fay–Herriot model is introduced to treat situations where small areas are divided in two groups and domain random effects have different variances across the groups. The model is applicable to data having a large subset of domains where direct estimates of the variable of interest cannot be described in the same way as in its complementary subset of domains. This is generally the case when domains are constructed by crossing geographical characteristics with sex. Algorithms and formulas to fit the model, to calculate EBLUPs and to estimate mean squared errors are given. Monte Carlo simulation experiments are presented to illustrate the gain of precision obtained by using the proposed model and to get some practical conclusions. A motivating application to Spanish Labour Force Survey data is also given. 2012 BB 4 http://hdl.handle.net/11104/0200537 STATISTICSPROBABILITY 0.386 0.077 >10.0 0.00599 0.284 1757 285 0.483 Q3 6.246 6.466 Q4 Q4 2011 000284884400002 WOS cav_un_epca*0252520 Communications in Statistics - Theory and Methods 0361-0926 1532-415X Roč. 40 č. 5 2011 785 797 Taylor & Francis