DFBETAS (standardized difference of the beta) is a measure that standardizes the absolute difference in parameter estimates between a (mixed effects) regression model based on a full set of data, and a model from which a (potentially influential) subset of data is removed. A value for DFBETAS is calculated for each parameter in the model separately. This function computes the DFBETAS based on the information returned by the influence() function.
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model |
An object as returned by the influence() function, containing the altered estimates of a mixed effects regression model |
parameters |
Used to define a selection of parameters. If parameters=0 (default), DFBETAS is calculated for all parameters in the model |
sort |
If |
to.sort |
Specify on which variable the DFBETAS must be sorted. If only one variable present (either in the model, or due to the selection specified in |
abs |
If |
... |
Currently not used |
A matrix is returned, containing DFBETAS-values for each (selected) fixed parameter of the model, and separately for each evaluated set of influential data.
Rense Nieuwenhuis, Ben Pelzer, Manfred te Grotenhuis
Nieuwenhuis, R., Te Grotenhuis, M., & Pelzer, B. (2012). Influence.ME: tools for detecting influential data in mixed effects models. R Journal, 4(2), 38???47.
Belsley, D.A., Kuh, E. & Welsch, R.E. (1980). Regression Diagnostics. Identifying Influential Data and Source of Collinearity. Wiley.
Snijders, T.A. & Bosker, R.J. (1999). Multilevel Analysis, an introduction to basic and advanced multilevel modeling. Sage.
Van der Meer, T., Te Grotenhuis, M., & Pelzer, B. (2010). Influential Cases in Multilevel Modeling: A Methodological Comment. American Sociological Review, 75(1), 173-178.
influence.mer
, cooks.distance.estex
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