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Thread: Mixed effects model residual analysis (help!)

  1. #1
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    Mixed effects model residual analysis (help!)




    Hello,

    I have little experience with mixed-effects models and could do with some help
    when it comes to checking model assumptions.

    I am using the 'lme()' function from the 'nlme' library in R to test the fixed
    effects of a repeated measures design. Given a pair of sounds (A and B), each
    subject was asked to match the loudness of both sounds by adjusting the amplitude of the variable sound.
    A number of different pairs were tested, with both A and B as the
    variable, and each subject was tested twice in every condition. There are a
    total of 160 observations per subject, and 14 participants in all.

    Dependent variable: amplitudeDifference
    Independent variables: pairOfSounds, variable

    The model:
    amplitudeDifference ~ pairOfSounds + variable + interaction + (1|Subject/pairOfSounds/variable)

    where '(1|Subject/pairOfSounds/variable)' allows for random intercepts of the
    factors within each subject.

    I have built the model up by AIC/BIC and likelihood ratio tests (method =
    "ML"). Residual plots for the within-group errors can be found here:
    goo.gl/jfTeKG

    The top left plot shows standardised residuals vs fitted values. I don't see any
    systematic pattern in the residuals, so I assume that the constant variation assumption
    is valid, although further inspection of the subject-by-subject residuals do
    show some unevenness. I did try to apply weights to model this but lme() failed to
    converge. In conjunction with the top right plot, I have no reason to suspect
    non-linearities.

    My main concern is the lower left qqplot which reveals that the residuals are
    heavy-tailed. I'm not sure where to go from here. From reading Pinheiro and Bates
    (2000, p. 180), the
    fixed-effects tests tend to be more conservative when the tails are
    symmetrically distributed. So perhaps I'm OK if the p-values are very low?

    The level two and three random effects show a similar departure from normality.

    Any help is much appreciated and thanks for your time in reading this.

  2. #2
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    Re: Mixed effects model residual analysis (help!)


    Hi,

    Can any one help with this? Even if just taking a quick scan over my residual plots.

    I have attached an image in case the link is causing problems.

    Thanks again.
    Attached Images

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