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Adaptive inference for multi-stage survey data

Journal Article


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.

Publication Date


  • 2010

Citation


  • 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.

Scopus Eid


  • 2-s2.0-77954827799

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/3388

Number Of Pages


  • 16

Start Page


  • 1334

End Page


  • 1350

Volume


  • 39

Issue


  • 7

Place Of Publication


  • http://www.tandf.co.uk/journals/titles/03610918.asp

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.

Publication Date


  • 2010

Citation


  • 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.

Scopus Eid


  • 2-s2.0-77954827799

Ro Metadata Url


  • http://ro.uow.edu.au/infopapers/3388

Number Of Pages


  • 16

Start Page


  • 1334

End Page


  • 1350

Volume


  • 39

Issue


  • 7

Place Of Publication


  • http://www.tandf.co.uk/journals/titles/03610918.asp