influence.ME is an R package for detecting influential data in multilevel regression models (or, mixed effects models as they are referred to in the R community). The application of multilevel models has become common practice, but the development of diagnostic tools has lagged behind. Hence, we developed influence.ME, which calculates standardized measures of influential data for the point estimates of generalized multilevel models, such as DFBETAS, Cook’s distance, as well as percentile change and a test for changing levels of significance. influence.ME calculates these measures of influence while accounting for the nesting structure of the data. A paper detailing this package was published in the R Journal (available from the R Journal (.PDF) and my researchgate.net profile).

influence.ME depends on lme4. As the authors of lme4 have completely revised the inner workings of lme4 and are currently releasing version 1.0, influence.ME required an update to maintain forward compatibility with lme4. I just uploaded version 0.9.3 of influence.ME to CRAN, which will be available soon. This version should work with the new lme4, but if you happen to run into any problems please contact me.