R help - Jan 2006 - log-linear analysis - calculate treatment effects

Dear all,

I have run a hierarchical log-linear analysis using loglin {stats}  
and came up with a specific model. loglin returns me the parameter  
estimates giving me an idea in which direction the observed  
frequencies deviate from the expected ones for my different factors.  
To assess the significance of any such effects I would need to  
calculate the ratio of the log-linear parameter estimate to its  
standard error (as explained in Howell: Statistical Methods for  
Psychology, 4th Edition, p. 637ff). Unfortunately, I have no idea and  
couldn't find out what this standard error refers to and how to  
calculate it or the ratio using R (well, the ratio is no problem if I  
have the standard error).

I would very much appreciate any help!

Thanks and best wishes, Cordula Becker

----------------------------------------------------
Dr. Cordula Becker

Department of Experimental Psychology
University of Cambridge
Downing Site
Cambridge  CB2 3EB
United Kingdom

Tel.: +44 (0)1223 339715
Email: cb486 at cam.ac.uk

http://vision.psychol.cam.ac.uk/cbecker/

Use multinom or glm instead.  The IFP algorithm used in loglin is not 
designed to find parameter estimates let alone standard errors.

Fitting log-linear models is discussed in all good books on R/S, e.g.
MASS (see the FAQ for full details).


On Tue, 17 Jan 2006, Becker Cordula wrote:
> Dear all,
>
> I have run a hierarchical log-linear analysis using loglin {stats}
> and came up with a specific model. loglin returns me the parameter
> estimates giving me an idea in which direction the observed
> frequencies deviate from the expected ones for my different factors.
> To assess the significance of any such effects I would need to
> calculate the ratio of the log-linear parameter estimate to its
> standard error (as explained in Howell: Statistical Methods for
> Psychology, 4th Edition, p. 637ff). Unfortunately, I have no idea and
> couldn't find out what this standard error refers to and how to
> calculate it or the ratio using R (well, the ratio is no problem if I
> have the standard error).
>
> I would very much appreciate any help!
>
> Thanks and best wishes, Cordula Becker
>
> ----------------------------------------------------
> Dr. Cordula Becker
>
> Department of Experimental Psychology
> University of Cambridge
> Downing Site
> Cambridge  CB2 3EB
> United Kingdom
>
> Tel.: +44 (0)1223 339715
> Email: cb486 at cam.ac.uk
>
> http://vision.psychol.cam.ac.uk/cbecker/
>
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> R-help at stat.math.ethz.ch mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide!
http://www.R-project.org/posting-guide.html
>
-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595