Thanks again Peter. What about the argument that because low R square (e.g. 
R^2=0.2) indicated the model variance was not sufficiently explained by the 
factors in the model, there might be additional factors that should be 
identified and included in the model. And If these additional factors were 
indeed included, it might change the significance for the factor of interest 
that previously showed significant coefficient. In other word, if R square is 
low, the significant coefficient observed is not trustworthy.

What's your opinion on this argument?

Many thanks!

John



________________________________
 From: peter dalgaard <pda...@gmail.com>

Cc: "r-help@r-project.org" <r-help@r-project.org> 
Sent: Monday, May 7, 2012 11:43 PM
Subject: Re: [R] low R square value from ANCOVA model


On May 8, 2012, at 08:34 , array chip wrote:

> Thank you Peter, so if I observe a significant coefficient, that significance 
> still holds because the standard error of the coefficient has taken the 
> residual error (which is large because large R square) into account, am I 
> correct?

In essence, yes. One might quibble over the use of "large because", but it's 
not important for the main point.

-pd

> John
> From: peter dalgaard <pda...@gmail.com>

> Cc: "r-help@r-project.org" <r-help@r-project.org> 
> Sent: Monday, May 7, 2012 11:07 PM
> Subject: Re: [R] low R square value from ANCOVA model
> 
> 
> 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]]
> > 
> > ______________________________________________
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> > and provide commented, minimal, self-contained, reproducible code.
> 
> -- 
> Peter Dalgaard, Professor,
> Center for Statistics, Copenhagen Business School
> Solbjerg Plads 3, 2000 Frederiksberg, Denmark
> Phone: (+45)38153501
> Email: pd....@cbs.dk  Priv: pda...@gmail.com
> 
> 
> 
> 
> 
> 
> 
> 
> 
> 

-- 
Peter Dalgaard, Professor
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd....@cbs.dk  Priv: pda...@gmail.com
        [[alternative HTML version deleted]]

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