If you look on my website on the favourite links page there is a link to an electronic stats book there and this book has a really good section on repeated measures with nested design. http://sites.google.com/site/deborahhilton/ Thanks Deborah
An appropriate method of analyzing longitudinal (repeated-measures) data, with the flexibility to identify and separate the relative contribution of confounding factors.It´s an extension of ordinary multiple regression, where the data have a hierarchical or clustered structure. In addition to describing the population mean response, the method recognizes and describes variation around the mean at both levels; e.g., at level 2, individuals have their own growth rates in response to a stimulus that vary randomly around the underlying population response, and, at level 1, each individual’s observed measurements may vary around their own growth trajectory.
You can look for example of the discussion of fundamental assumptions of rpeated mesures ANOVA and alternative hierarchical models in Kristensen M, Hansen T. Statistical analyses of repeated measures in physiological research: a tutorial. Adv Physiol Educ. 2004 Dec;28(1-4):2-14., which is available free in the journal site.
How would you deal with two repeated measures but within the same experimental set-up? Lets say 14 hours continuous measurements for 10 weeks where hour and week both are repeated. Any ideas, suggestions or references please?