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Regressor and random‐effects dependencies in multilevel models

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  • Peter Ebbes
  • Ulf Böckenholt
  • Michel Wedel

Abstract

The objectives of this paper are (1) to review methods that can be used to test for different types of random effects and regressor dependencies, (2) to present results from Monte Carlo studies designed to investigate the performance of these methods, and (3) to discuss estimation methods that can be used when some but not all of the random effects and regressor independence assumptions, are violated. Because current methods are limited in various ways, we will also present a list of open problems and suggest solutions for some of them. As we will show, the issue of regressor random‐effects independence has received some attention in the econometrics literature, but this important work has had little impact on current research practices in the social and behavioral sciences.

Suggested Citation

  • Peter Ebbes & Ulf Böckenholt & Michel Wedel, 2004. "Regressor and random‐effects dependencies in multilevel models," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 58(2), pages 161-178, May.
    • Handle: RePEc:bla:stanee:v:58:y:2004:i:2:p:161-178
    DOI: 10.1046/j.0039-0402.2003.00254.x
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    References listed on IDEAS

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    5. Nelson, Charles R & Startz, Richard, 1990. "Some Further Results on the Exact Small Sample Properties of the Instrumental Variable Estimator," Econometrica, Econometric Society, vol. 58(4), pages 967-976, July.
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