[R] How to z-standardize for subgroups?

[Karsten Wolf]

Hi Jorge, Chuck and Kane,
thanks for your input!
The following code based on Jorge's answer did the trick to  
standardize for subgroups within multiple columns:

# define a standardize function, but you could also define your custom  
standardize function here
z.mean.sd <- function(data){
	return.values <- (data  - mean(data, na.rm = TRUE)) / (sd(data, na.rm  
= TRUE))
	return(return.values)
}

# assume there is some data.frame called sole.data with a group factor  
sole.data$studie already read into R
sole.data <- read.csv2("SoLe.dat")
attach(sole.data)
# assume I have created a subset of the data.frame cor.vars with only  
some of the vars needed to be standardized
cor.vars <- data.frame(var02, var04, var07, var10, var17, var24, var 36)

z.cor.vars <- apply(cor.vars, 2, tapply, sole.data$studie, z.mean.sd)
z.cor.vars <- sapply(z.cor.vars, unlist, USE.NAMES = FALSE)
z.cor.vars

BUT then Chuck's answer was much more elegant than my first woodpecker  
solution

apply(iris[,1:4], 2, function(x){ave(x, iris$Species, FUN = scale)})

could be translated into

apply(sole.data[,c(2,4,7,10,17,24,36)], 2, function(x){ave(x,sole.data 
$studie, FUN=scale)})

Thanks for the beauty of this code with an anonymous function call :)

-karsten



Am 29.11.2009 um 16:47 schrieb Jorge Ivan Velez:

> Hi Karsten,
>
> Let me assume your data is called d. If I understood what you are  
> trying to do, the following might help:
>
> res <- apply(d, 2, tapply, d$group, scale)
> res
>
> See ?apply, ?tapply and ?scale for more information.
>
> HTH,
> Jorge
>
>
> On Sun, Nov 29, 2009 at 10:41 AM, Karsten Wolf <> wrote:
> Hi folks,
> I have a dataframe df.vars with the follwing structure:
>
>
> var1   var2   var3   group
>
> Group is a factor.
>
> Now I want to standardize the vars 1-3 (actually - there are many  
> more) by class, so I define
>
> z.mean.sd <- function(data){
>        return.values <- (data  - mean(data)) / (sd(data))
>        return(return.values)
> }
>
> now I can call for each var
>
> z.var1 <- by(df.vars$var1, group, z.mean.sd)
>
> which gives me the standardised data for each subgroup in a list  
> with the subgroups
>
> z.var1 <- unlist(z.var1)
>
> then gives me the z-standardised data for var1 in one vector. Great!
>
> Now I would like to do this for the whole dataframe, but probably I  
> am not thinking vectorwise enough.
>
> z.df.vars <- by(df.vars, group, z.mean.sd)
>
> does not work. I banged my head on other solutions trying out sapply  
> and tapply, but did not succeed. Do I need to loop and put  
> everything together by hand? But I want to keep the columnnames in  
> the vector…
>
> -karsten
>
>
> ---------------------------------------------------------------------------------------------
> Karsten D. Wolf
> Didactical Design of Interactive
> Learning Environments
> Universität Bremen - Fachbereich 12
> web: http://www.ifeb.uni-bremen.de/wolf/
>
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