  I have a spectrophotometric dataset with repeated measures of a value 
at 200 wavelengths for each of  150 individuals.

I would like to use the repeated samples to at each wavelength to look 
at measurement/observer error, compared to difference between 
individuals error

I have looked at doing this with icc{irr} or using an anova approach, 
but I am unclear how to acheive this given that there is a nested 
structure- the value varies between wavelengths within individuals.

Many thanks

Nevil Amos

data is structured thus:

>       ANWC_NO Wavelength Repeat    value
> 1       00239        300       r1 0.079501
> 2       00239        302       r1 0.084113
> 3       00239        304       r1 0.087697
> 202     11157        300       r1 0.008449
> 203     11157        302       r1 0.009489
> 204     11157        304       r1 0.010142
> 403     11158        300       r1 0.026999
> 404     11158        302       r1 0.029612
> 405     11158        304       r1 0.030271
> 604     11159        300       r1 0.032784
> 66934   38711        300       r3 0.062081
> 66935   38711        302       r3 0.065137
> 66936   38711        304       r3 0.067092
> 67135   38712        300       r3 0.029389
> 67136   38712        302       r3 0.030192
> 67137   38712        304       r3 0.030860
> 67336   38993        300       r3 0.045720
> 67337   38993        302       r3 0.048060
> 67338   38993        304       r3 0.051898
> 67537   38994        300       r3 0.051815
> 67538   38994        302       r3 0.055162


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