To handle the correlations, you can treat individuals as random blocks. So
you have a mixed model with measurement technique crossed with measured
attribute and random intercepts for each individual. You can fit this with
lmer() in the lme4 package. Keep in mind there are a number of variations
I would like to estimate the difference between two measurement techniques.
With both techniques, 4 measurements were obtained in each of 15
individuals. (These are not *repeated* measurements though - each of the 4
is of a different attribute). The naive approach would be a paired t-test,
but of
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