Within and between estimates in random-effects models: Advantages and drawbacks of correlated random effects and hybrid models

Schunck R (2013)
The Stata Journal 13(1): 65-76.

Journal Article | Published | English

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Abstract
Correlated random-effects (Mundlak, 1978, Econometrica 46: 69–85; Wooldridge, 2010, Econometric Analysis of Cross Section and Panel Data [MIT Press]) and hybrid models (Allison, 2009, Fixed Effects Regression Models [Sage]) are attractive alternatives to standard random-effects and fixed-effects models because they provide within estimates of level 1 variables and allow for the inclusion of level 2 variables. I discuss these models, give estimation examples, and address some complications that arise when interaction effects are included.
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Schunck R. Within and between estimates in random-effects models: Advantages and drawbacks of correlated random effects and hybrid models. The Stata Journal. 2013;13(1):65-76.
Schunck, R. (2013). Within and between estimates in random-effects models: Advantages and drawbacks of correlated random effects and hybrid models. The Stata Journal, 13(1), 65-76.
Schunck, R. (2013). Within and between estimates in random-effects models: Advantages and drawbacks of correlated random effects and hybrid models. The Stata Journal 13, 65-76.
Schunck, R., 2013. Within and between estimates in random-effects models: Advantages and drawbacks of correlated random effects and hybrid models. The Stata Journal, 13(1), p 65-76.
R. Schunck, “Within and between estimates in random-effects models: Advantages and drawbacks of correlated random effects and hybrid models”, The Stata Journal, vol. 13, 2013, pp. 65-76.
Schunck, R.: Within and between estimates in random-effects models: Advantages and drawbacks of correlated random effects and hybrid models. The Stata Journal. 13, 65-76 (2013).
Schunck, Reinhard. “Within and between estimates in random-effects models: Advantages and drawbacks of correlated random effects and hybrid models”. The Stata Journal 13.1 (2013): 65-76.
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