Hi,

Thanks to everyone who answered my query concerning references for Repeated
Measures analysis:

>Could you please recommend some good references on Repeated Measures
>Analysis. This is an area of statistics I have not looked at since
finishing
>university (15 odd years ago) and now need to refresh my memory, and find
>out about what new methodologies are available.

I have attached a summary of the responses below.

Martyn


-----Original Message-----
See "Multilevel Analysis" by Snijders & Bosker 2002.

-----Original Message-----
Experiments in ecology Underwood

Design and analysis of experiments Montgomery

-----Original Message-----
If you want to go beyond repeated measures ANOVA, you could have a look at:
Collins, L. M. and Sayer, A. G. (2001). New Methods for the Analysis of
Change. Washington, DC, American Psychological Association.

-----Original Message-----
The Analysis of Longitudinal Data (Oxford Statistical Science S.)
Peter J. Diggle, Patrick Heagerty, Kung-Yee Liang, Scott Zeger

Models for Repeated Measurements (Oxford Statistical Science S.)
J.K. Lindsey


Random Coefficient Models (Oxford Statistical Science S.)
C. Longford


Analysis of Repeated Measures (Monographs on Statistics & Applied
Probability)
M.J. Crowder, D.J. Hand

-----Original Message-----
Littell, R.C., Milliken, G.A., Stroup, W.W., & Wolfinger, R.D. (1996). SAS
system for mixed models. Cary, NC: SAS Institute. (Littell, Milliken,
Stroup, & Wolfinger, 1996)

-----Original Message-----
Littell RC, Henry PR, Ammerman CB "Statistical analysis of repeated measures
data using SAS procedures"
JOURNAL OF ANIMAL SCIENCE 76 (4): 1216-1231 APR 1998

isn't bad - a bit of a sales job for the mixed effects models approach, but
it does also talk about other approaches.

For a back-to-basics approach, Roger Mead's "Design of Experiments"
(CUP, 1990?) has a section on issues in analysis of repeated measures in the
chapter on split-plot designs

Both are really only starting points;  beyond those you might try the book
by Crowder and Hand (don't recall the exact title, but it was something
obvious like "Analysis of Repeated Measures") which I found quite a useful
reference on traditional (pre mixed effect models) approaches;  or Diggle,
Liang and Zieger, which a lot of people seem to cite

-----Original Message-----
I really like Prescott and Brown's text (publisher is Wiley). They run a
good course in Edinburgh on mixed modelling too.

-----Original Message-----
I had much fun in reading by Jim Lindsey: Models for repeated
measurements,Oxford, and also got lots of help from the author
http://alpha.luc.ac.be/~jlindsey  . I think it would be necessary to work in
R, but that is should not discredit the book IMHO.

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