  The trace plot is seldom used in meta-analysis, yet it is a very informative
plot. In this article we define and illustrate what the trace plot is, and
discuss why it is important. The Bayesian version of the plot combines the
posterior density of tau, the between-study standard deviation, and the
shrunken estimates of the study effects as a function of tau. With a small or
moderate number of studies, tau is not estimated with much precision, and
parameter estimates and shrunken study effect estimates can vary widely
depending on the correct value of tau. The trace plot allows visualization of
the sensitivity to tau along with a plot that shows which values of tau are
plausible and which are implausible. A comparable frequentist or empirical
Bayes version provides similar results. The concepts are illustrated using
examples in meta-analysis and meta-regression; implementaton in R is
facilitated in a Bayesian or frequentist framework using the bayesmeta and
metafor packages, respectively.
