  Whilst most psychological research focuses on differences in means, a growing
body of literature demonstrates the value of considering differences in
intra-individual variability. Compared to the number of methods available for
analyzing mean differences, there is a paucity of methods available for
analyzing intra-individual variability, particularly when variability is
treated as a predictor. In the present article, we first reviewed methods of
analyzing intra-individual variability as an outcome, including the individual
standard deviation (ISD) and some recent methods. We then introduced a novel
Bayesian method for analyzing intra-individual variability as a predictor. To
make this method easily accessible to the research community, we developed an
open source R package, VARIAN. To compare the accuracy of parameter estimates
using the proposed Bayesian analysis against the ISD as a predictor in a
regression, we carried out a simulation study. We then demonstrated, using
empirical data, how the estimated intra-individual variability derived from the
proposed Bayesian analysis can be used to answer the following two questions:
(1) is intra-individual variability in daily time-in-bed associated with
subjective sleep quality? (2) does subjective sleep quality mediate the
association between time-in-bed variability and depressive symptoms? We
concluded with a discussion of methodological and practical considerations that
can help guide researchers in choosing methods for evaluating intra-individual
variability.
