influence.ME (0.6.1)

Tools for recognizing influential data in mixed models.

influence.ME provides a collection of tool for calculating measures of influential data for mixed effects models. The basic rationale behind identifying influential data is that when iteratively single units are omitted from the data, models based on these data should not produce substantially different estimates. To standardize the assessment of how influential a (single group of) observation(s) is, several measures of influence are common practice. First, DFBETAS is a standardized measure of the absolute difference between the estimate with a particular case included and the estimate without that particular case. Second, Cook's distance provides an overall measurement of the change in all parameter estimates, or a selection thereof.

Maintainer: Rense Nieuwenhuis
Author(s): Rense Nieuwenhuis, Ben Pelzer, Manfred te Grotenhuis

License: GPL-3

Uses: lattice, lme4

Released almost 10 years ago.