Inference of Adaptive methods for Multi-Stage skew-t Simulated Data

Loai M. A. Al-Zou’bi, Amer I. Al-Omari, Ahmad M. Al-Khazalah, Raed A. Alzghool

Abstract


Multilevel models can be used to account for clustering in data from multi-stage surveys. In some cases, the intra-cluster correlation may be close to zero, so that it may seem reasonable to ignore clustering and fit a single level model. This article proposes several adaptive strategies for allowing for clustering in regression analysis of multi-stage survey data. The approach is based on testing whether the cluster-level variance component is zero. If this hypothesis is retained, then variance estimates are calculated ignoring clustering; otherwise, clustering is reflected in variance estimation. A simple simulation study is used to evaluate the various procedures.

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European Scientific Journal (ESJ)

 

ISSN: 1857 - 7881 (Print)
ISSN: 1857 - 7431 (Online)

 

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