This note concerns mixed-effect (MFX) analyses in multisession functional magnetic
resonance imaging (fMRI) studies. It clarifies the relationship between mixed-effect
analyses and the two-stage "summary statistics" procedure (Holmes, A.P., Friston,
K.J., 1998. Generalisability, random effects and population inference. NeuroImage
7, S754) that has been adopted widely for analyses of fMRI data at the group level.
We describe a simple procedure, based on restricted maximum likelihood (ReML) estimates
of covariance components, that enables full mixed-effects analyses in the context
of statistical parametric mapping. Using this procedure, we compare the results of
a full mixed-effects analysis with those obtained from the simpler two-stage procedure
and comment on the situations when the two approaches may give different results.