[R] rms package-superposition prediction curve of ols and data points

Frank Harrell f.harrell at vanderbilt.edu
Wed Jun 27 03:40:00 CEST 2012


This is what the addpanel argument to plot.Predict is for, something along
the lines of

ap <- function(...) lpoints(age, weight)
plot(Predict(. . .), addpanel=ap)

Frank


David Winsemius wrote
> 
> On Jun 26, 2012, at 11:29 AM, Sarah Goslee wrote:
> 
>> You could use points() instead of plot() for the second command.
> 
> 
> Ummm. Maybe not. I think think that plot.Predict uses lattice  
> graphics. You may need to use trellis.focus() followed by lpoints().  
> Or use the "+" operation with suitable objects.
> 
> -- 
> David.
> 
> 
>>
>> Sarah
>>
>> On Tue, Jun 26, 2012 at 8:37 AM, achaumont <agnes.chaumont@>  
>> wrote:
>>> Hello,
>>>
>>> I have a question about the “plot.predict” function in Frank  
>>> Harrell's rms
>>> package.
>>> Do you know how to superpose in the same graph the prediction curve  
>>> of ols
>>> and raw data points?
>>> Put most simply, I would like to combine these two graphs:
>>>
>>>>  fit_linear <- ols (y4 ~ rcs(x2,c(5,10,15,20,60,80,90)), x=TRUE,  
>>>> y=TRUE)
>>>> p <- Predict(fit_linear,x2,conf.int=FALSE)
>>>> plot (p, ylim =c(-2,0.5), xlim=c(0,100))              # graph n°1
>>>
>>>> z <- plot  
>>>> (x2,y4,ylim=c(-2,0.5),xlim=c(0,100),type="p",lwd=6,col="blue")
>>>> # graph n°2
>>>
>>> Thanks all,
>>>
>>> Agnès
>>>
>>>
>>>
>>
>>
>> -- 
>> Sarah Goslee
>> http://www.functionaldiversity.org
>>
>> ______________________________________________
>> R-help@ 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.
> 
> David Winsemius, MD
> West Hartford, CT
> 
> ______________________________________________
> R-help@ 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.
> 


-----
Frank Harrell
Department of Biostatistics, Vanderbilt University
--
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