Small Area Estimation Under Linear and GeneralizedLinear Mixed Models With Time and Area Effects

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Empirical best prediction under area-level Poisson mixed models (2016, methodology): “…linear mixed model (GLMM) with logit link function, and with combination of Penalized Quasi-Likelihood (PQL) and REML for estimation of unknown parameters have been considered by Saei and Chambers (2003), Johnson et al. (2010), López-Vizcáıno et al. (2013) and López-Vizcáıno et al. (2015).”
Small area estimation of labour force indicators under a multinomial model with correlated time and area effects (2015, methodology): “The combined algorithm was first introduced by Schall (1991) and later used by Saei and Chambers (2003), Molina et al. (2007) and Herrador et al. (2009) in applications of generalized linear mixed models to small area estimation problems.”
Multinomial-based small area estimation of labour force indicators* (2013, methodology): “The combined algorithm was first introduced by Schall (1991) and later used by Saei and Chambers (2003) and Molina et al. (2007) in applications of generalized linear mixed models to SAE problems.”
Small area estimation in the presence of correlated random area effects (2009, background): “…Random Area Effects Monica Pratesi1 and Nicola Salvati1 This article is a contribution to the discussion on the utility of spatial models in the context of Small Area Estimation (SAE) (see Cressie 1991; Pfeffermann 2002; Saei and Chambers 2003, 2005; Singh et al. 2005; Pratesi and Salvati 2008).”