  We propose simple inferential approaches for the fixed effects in complex
functional mixed effects models. We estimate the fixed effects under the
independence of functional residuals assumption and then bootstrap independent
units (e.g. subjects) to estimate the variability of and conduct inference in
the form of hypothesis testing on the fixed effects parameters. Simulations
show excellent coverage probability of the confidence intervals and size of
tests. Methods are motivated by and applied to the Baltimore Longitudinal Study
of Aging (BLSA), though they are applicable to other studies that collect
correlated functional data.
