2026-06-27T23:22:42Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/242912023-08-10T19:20:00Zcom_20.500.14352_14col_20.500.14352_15

Marhuenda García, Yolanda Morales, D. Pardo Llorente, María del Carmen 2023-06-18T06:49:06Z 2023-06-18T06:49:06Z 2016-01 0233-1888 http://dx.doi.org10.1080/02331888.2015.1016026 https://hdl.handle.net/20.500.14352/24291 http://www.tandfonline.com/doi/abs/10.1080/02331888.2015.1016026 http://www.tandfonline.com/ The Fay-Herriot model is a linear mixed model that plays a relevant role in small area estimation (SAE). Under the SAE set-up, tools for selecting an adequate model are required. Applied statisticians are often interested on deciding if it is worthwhile to use a mixed effect model instead of a simpler fixed-effect model. This problem is not standard because under the null hypothesis the random effect variance is on the boundary of the parameter space. The likelihood ratio test and the residual likelihood ratio test are proposed and their finite sample distributions are derived. Finally, we analyse their behaviour under simulated scenarios and we also apply them to real data eng restricted access Tests for the variance parameter in the Fay–Herriot model journal article