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Abstract Details
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Activity Number:
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464
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Type:
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Contributed
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Date/Time:
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Wednesday, August 1, 2012 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistical Computing
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| Abstract - #305411 |
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Title:
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Implementation of Influence Diagnostics for Linear Mixed Effects Models in R
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Author(s):
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Andrzej Galecki*+ and Tomasz Burzykowski
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Companies:
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University of Michigan and Hasselt University
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Address:
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, Ann Arbor, MI, 48109,
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Keywords:
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R ;
lme function ;
nlme package ;
mixed effects models ;
influence diagnostics
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Abstract:
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Influence diagnostics are formal techniques allowing for the identification of observations that exert substantial influence on the estimates of fixed effects and variance covariance parameters. The idea of influence diagnostics for a given observation is to quantify the effect of omission of this observation from the data on the results of the model fit. To this aim, the concept of likelihood displacement is used. We have developed a function in R, which allows performing influence diagnostics for linear mixed effects models fitted using the lme() function from the nlme package. The use of the new function is illustrated using data from a randomized clinical trial.
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