Title

Adaptive inference for multi-stage survey data

RIS ID

32985

Publication Details

Al-zou'bi, L. Mahmoud., Clark, R. Graham. & Steel, D. G. (2010). Adaptive inference for multi-stage survey data. Communications in Statistics: Simulation and Computation, 39 (7), 1334-1350.

Abstract

Multi-level models can be used to account for clustering in data from multi-stage surveys. In some cases, the intraclass 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 PSU-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.

Please refer to publisher version or contact your library.

Share

COinS
 

Link to publisher version (DOI)

http://dx.doi.org/10.1080/03610918.2010.493273