, Volume 68, Issue 3, pp 309–329 | Cite as

Selection bias in linear mixed models

  • Leonardo Grilli
  • Carla Rampichini


The paper investigates the consequences of sample selection in multilevel or mixed models, focusing on the random intercept two-level linear model under a selection mechanism acting at both hierarchical levels. The behavior of sample selection and the resulting biases on the regression coefficients and on the variance components are studied both theoretically and through a simulation study. Most theoretical results exploit the properties of Normal and Skew-Normal distributions. The analysis allows to outline a taxonomy of sample selection in the multilevel framework that can support the qualitative assessment of the problem in specific applications and the development of suitable techniques for diagnosis and correction.

Key Words

Clustered data Multilevel model Random effects Sample selection Skew-Normal distributions Truncation 


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Copyright information

© Sapienza Università di Roma 2010

Authors and Affiliations

  1. 1.Dipartimento di Statistica “GParenti” Università di FirenzeFirenzeItalia

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