Empirical Best Prediction for Small Area Inference with Binary Data

By Jiming Jiang, Partha Lahiri. 2001

114 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/cc25de3640816fa72f24798ca989be2b99214c79

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Citations in the corpus

Semiparametric inference in generalized mixed effects models (2008, unknown): “Malec, Sedransk, Moriarity, and LeClere 1997; Ghosh, Natarajan, Stroud, and Carlin, 1998; Butar and Lahiri, 2003) or using frequentist methodology (Prasad and Rao, 1990; Jiang and Lahiri, 2001; Jiang, 2003; Das, Sedransk, Moriarity, and LeClere, 2004; González-Manteiga, Lombard́ıa, Molina, Morales, ”
Estimation of Finite Population Domain Means (2006, methodology): “Throughout this section, we assume that ζi = Em(Ȳi,P|vi), which holds under, for example, the normal mixed linear model of Prasad and Rao (1999) and the mixed logistic model of Jiang and Lahiri (2001).”
Small area estimation of poverty proportions under unit-level temporal binomial-logit mixed models (2017, unknown): “The statistical methodology is taken and adapted from Jiang and Lahiri (2001) and Jiang (2003), where EBPs of functions of fixed effects and small area specific random effects were developed in the context of logisticmixedmodels andGLMM, respectively.”
Mixed model prediction and small area estimation (2006, background): “Jiang and Lahiri (2001) considered the following mixed logistic model for small area estimation.”
Empirical best prediction under area-level Poisson mixed models (2016, methodology): “The statistical methodology is taken and adapted from Jiang and Lahiri (2001) and Jiang (2003), where EBPs of functions of fixed effects and small area specific random effects were developed in the context of logistic mixed models and GLMM respectively.”
Empirical Best Prediction Under Unit-Level Logit Mixed Models (2016, methodology): “In particular, some properties established by Jiang (1998, 2003) and Jiang and Lahiri (2001) are employed in the article to derive the approximation to the model-based MSE of the EBP, conditional on a specified model and without random effects at levels finer than domain.”
A unified jackknife theory for empirical best prediction with M-estimation (2002, methodology): “This is because to compute the MSE estimator of Jiang and Lahiri (2001) one has to obtain analytic forms of the first and second derivatives involved (numerical differentiation is unstable), which is not easy when the model gets complicated, and errors are often made in derivation and programming.”
Small Area Estimation‐New Developments and Directions (2002, methodology): “The model defined by (4.1) has been studied more recently by Jiang and Lahiri (1998).”
Model Selection by Testing for the Presence of Small-Area Effects, and Application to Area-Level Data (2011, methodology): “Small-area estimation of the proportions based on a logistic mixed linear model has been considered earlier by MacGibbon and Tomberlin (1989), Farrell, MacGibbon, and Tomberlin (1997), and Jiang and Lahiri (2001).”