On May 8, 2012, at 05:10 , array chip wrote:
> Hi, what does a low R-square value from an ANCOVA model mean? For example,
if the R square from the model is about 0.2, does this mean the results should
NOT be trusted? I checked the residuals of the model, it looked fine...
It just means that your model has low predictive power (at the individual
level). I.e. the noise (error) part of the model is large relative to the signal
(systematic part). Statistical inferences are not compromised by that, except of
course that large error variation is reflected in large standard errors of
estimated regression coefficients.
>
> Thanks for any suggestion.
>
> John
> [[alternative HTML version deleted]]
>
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