We apply the generalized cluster bootstrap to both Gaussian quasi-likelihood and robust estimates in the context of highly unbalanced clustered data. We compare it with the transformation bootstrap where the data are generated by the random effect and transformation models and all the random...

The generalized persistence (GP) model, developed in the context of estimating “value added” by individual teachers to their students’ current and future test scores, is one of the most flexible value-added models in the literature. Although developed in the educational setting, the GP...

A prediction interval is derived for the BLUP (Best Linear Unbiased Predictor) in mixed models involving a single random effect of interest, using the generalized inference approach. The resulting prediction interval is referred to as a generalized prediction interval. The solution in the case...

In this article we consider the Two-Way ANOVA model with unequal cell frequencies without the assumption of equal error variances. For the problem of testing no interaction effects and equal main effects, we propose a parametric bootstrap (PB) approach and compare it with existing the...

Nonparametric bootstrapping for hierarchical data is relatively underdeveloped and not straightforward: certainly it does not make sense to use simple nonparametric resampling, which treats all observations as independent. We have provided some resampling strategies of hierarchical data, proved...

A framework for analyzing substitution and scale properties, and technical change from plant-level panel data is presented. Focus is on comparing the constant and random coefficient specification of the substitution and scale parameters and investigating the potential variation of the parameters...