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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