Publication: Avoiding "data snooping" in multilevel and mixed effects models
Avoiding "data snooping" in multilevel and mixed effects models
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Afshartous, D., & Wolf, M. (2007). Avoiding “data snooping” in multilevel and mixed effects models. Journal of the Royal Statistical Society: Series A, 170, 1035–1059. https://doi.org/10.1111/j.1467-985X.2007.00494.x
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Multilevel or mixed effects models are commonly applied to hierarchical data. The level 2 residuals, which are otherwise known as random effects, are often of both substantive and diagnostic interest. Substantively, they are frequently used for institutional comparisons or rankings. Diagnostically, they are used to assess the model assumptions at the group level. Inference on the level 2 residuals, however, typically does not account for "data snooping", i.e. for the harmful effects of carrying out a multitude of hypothesis tests at t
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- Afshartous, David
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Citations
Afshartous, D., & Wolf, M. (2007). Avoiding “data snooping” in multilevel and mixed effects models. Journal of the Royal Statistical Society: Series A, 170, 1035–1059. https://doi.org/10.1111/j.1467-985X.2007.00494.x
