Provides a collection of tools for detecting influential cases in generalized mixed effects models. It analyses models that were estimated using 'lme4'. The basic rationale behind identifying influential data is that when 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, such as Cook's Distance. In addition, we provide a measure of percentage change of the fixed point estimates and a simple procedure to detect changing levels of significance.
Package details 


Author  Rense Nieuwenhuis, Ben Pelzer, Manfred te Grotenhuis 
Maintainer  Rense Nieuwenhuis <rense.nieuwenhuis@sofi.su.se> 
License  GPL3 
Version  0.99 
URL  http://www.rensenieuwenhuis.nl/rproject/influenceme/ 
Package repository  View on CRAN 
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