Description Usage Arguments Value Author(s) References See Also Examples
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.
1 2 |
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
1 2 3 4 5 6 7 8 |
Loading required package: lme4
Loading required package: Matrix
Attaching package: 'influence.ME'
The following object is masked from 'package:stats':
influence
(Intercept) structure SES
6053 0.117362156 -1.177229e-01 -0.43620616
6327 -0.014977889 4.647880e-02 0.29696472
6467 0.015303877 2.370881e-02 0.05775058
7194 -0.003883099 4.751635e-03 -0.02188325
7472 -1.190161877 1.149068e+00 0.21322677
7474 -0.354841538 4.140141e-01 0.05526341
7801 0.031771248 -3.176227e-02 -0.23173526
7829 0.295080757 -3.436108e-01 -0.24108880
7930 -0.008598692 2.732134e-02 0.21506175
24371 -0.036826313 2.961490e-02 0.31290762
24725 -0.069315786 2.455829e-02 0.34234755
25456 -0.005099626 1.103001e-03 0.05366766
25642 0.037636913 -4.268351e-02 -0.31941096
26537 -0.071377655 6.080783e-02 -0.05793571
46417 0.036345105 2.862716e-02 -0.03768676
47583 -0.093250535 1.075697e-01 0.29583534
54344 0.796429887 -9.300953e-01 -0.61254221
62821 0.642708314 -5.779312e-01 -0.38613133
68448 -0.174042304 1.578268e-01 0.15286586
68493 -0.028074075 7.359803e-05 0.11335974
72080 0.034060154 -2.186994e-02 -0.18497495
72292 -0.028278685 1.924209e-02 0.24571091
72991 0.002482324 3.258969e-02 0.18290665
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