If you are using the latest version (4.5-25), you will see in rfNews() that 
that's the problem I need to fix.  The package was able to handle ordered 
factors, but some more stringent checks for factor levels consistency 
introduced in 4.5-23 broke the support for ordered factors in prediction.  

>From the code you've shown, it looks like you are just growing the forest to 
>evaluate variable importance or other things, instead of predicting other data 
>(since you set keep.forest=FALSE).  If that's the case, you should be fine, as 
>the problem only happens when you try to call predict() with models that 
>contain ordered factors as predictors.

(Ordered factors are basically treated as numerics in RF: trees only make use 
of ranks for numeric variables, so there's basically no difference between 
ordered factors and numeric variables as predictors.)

Andy 

From: Birgit Lemcke
> 
> Hello R-user!
> 
> I am running R 2.7.0 on a Power Book (Tiger). (I am still R and  
> statistics beginner)
> 
> I try to find the most important variables to divide my dataset as  
> given in a categorical variable.
> 
> code:
> 
> Test.rf4<-randomForest(Sex~.,na.action=na.roughfix, data=Subset4,  
> importance=TRUE, proximity=TRUE, ntree=10000, do.trace=1000,  
> keep.forest=FALSE)
> 
> My dataset contains also ordered factors classified as such.
> Is randomForest able to deal with it, does it change anything or is  
> there no difference in using factors or ordered factors?
> 
> Many thanks in advance
> 
> B.
> 
> Birgit Lemcke
> Institut für Systematische Botanik
> Zollikerstrasse 107
> CH-8008 Zürich
> Switzerland
> Ph: +41 (0)44 634 8351
> [EMAIL PROTECTED]
> 
> 175 Jahre UZH
> «staunen.erleben.begreifen. Naturwissenschaft zum Anfassen.»
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> 19. April 2008, 10.00 Uhr bis 02.00 Uhr
> Campus Irchel, Winterthurerstrasse 190, 8057 Zürich
> Weitere Informationen http://www.175jahre.uzh.ch/naturwissenschaft
> 
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