relative and absolute error variance across a variety of bootstrap procedures for each combination of conditions. It was found … suggested with respect to nested designs. This study provides support for the use of bootstrap procedures for estimating …

distribution of alpha by finite normal mixture model. We introduce the parametric bootstrap procedure to determine the number of …

(Rosenheck et al, 1997).In part III, we consider the combination of bootstrap and Bayes inferences. In the case of independent … identically distributed samples, the simple bootstrap yields confidence limits that are asymptotically correct to the first order … the bootstrap. A discrepancy statistic based on the difference of model and bootstrap estimates of variance is developed …

This study examines technical efficiency of Critical Access Hospitals (CAH) using a two-stage approach and bootstrap … second stage, efficiency scores are regressed on environmental variables using a truncated regression with bootstrap …. Alternatively, a double bootstrap procedure is used, where bias-corrected DEA efficiency scores, obtained by means of bootstrap in …

, factor based bootstrap approach is proposed for inferential issues in functional coefficient models. This approach can cope … with heterogeneous error distributions and is proven to hold asymptotically. In simulation studies factor based bootstrap … inference outperforms the wild bootstrap and pairs bootstrap approach according to its size features. Regarding current account …

Poisson regression in a log-linear model. The third one is a nonparametric approach based on bootstrap percentile confidence … computationally expensive and it has desirable Type I errors in most cases as well as good powers. The bootstrap-based method is the …