influence.ME (version 0.8.1)

ME.dfbetas: Compute the DFBETAS measure of influential data

Description

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 estex() function.

Usage

ME.dfbetas(estex, parameters = 0, plot=FALSE, sort=FALSE, to.sort=NA, abs=FALSE, ...)

Value

A matrix is returned, containing DFBETAS-values for each (selected) fixed parameter of the model, and separately for each evaluated set of influential data.

References

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.

See Also

estex, ME.cook

Examples

data(school23)
 model <- lmer(math ~ structure + SES  + (1 | school.ID), data=school23)

 alt.est <- estex(model, "school.ID")
 ME.dfbetas(alt.est)
 ME.dfbetas(alt.est, plot=TRUE, layout=c(1,3))