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Analytical Modeling in Complex Surveys of Work Practices

Author

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  • Jerome P. Reiter
  • Elaine L. Zanutto
  • Larry W. Hunter

Abstract

Quantitative industrial relations research frequently relies on data collected from large surveys of establishments that use complex sampling designs, such as stratified and unequal probability sampling. The authors analyze two complex surveys of establishments, the National Organizations Survey and the National Survey of Establishments. They discuss design-based (survey-weighted) and model-based (unweighted) strategies for analyzing these data. They show that the choice of strategy can affect inferences about parameters, and hence conclusions drawn from analyses. They discuss the advantages of model-based approaches that include independent variables corresponding to design features, such as functions of size measures or indicator variables for strata or clusters, relative to purely design-based approaches.

Suggested Citation

  • Jerome P. Reiter & Elaine L. Zanutto & Larry W. Hunter, 2005. "Analytical Modeling in Complex Surveys of Work Practices," ILR Review, Cornell University, ILR School, vol. 59(1), pages 82-100, October.
    • Handle: RePEc:sae:ilrrev:v:59:y:2005:i:1:p:82-100
    DOI: 10.1177/001979390505900105
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    References listed on IDEAS

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    7. Peter Cappelli & David Neumark, 2001. "Do “High-Performance†Work Practices Improve Establishment-Level Outcomes?," ILR Review, Cornell University, ILR School, vol. 54(4), pages 737-775, July.
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    Cited by:

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    2. Fakhfakh F. & Perotin V. & Gago M., 2009. "Productivity, Capital and Labor in Labor-Managed and Conventional Firms," Working Papers ERMES 0910, ERMES, University Paris 2.
    3. Corinne Perraudin & Héloïse Petit, & Antoine Rebérioux, 2013. "Worker Information and Firm Disclosure Analysis on French Linked Employer–Employee Data," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 52(1), pages 134-161, January.

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