R help - Nov 2009 - How to z-standardize for subgroups?

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
Universit?t Bremen - Fachbereich 12
web: http://www.ifeb.uni-bremen.de/wolf/

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/
>
> ______________________________________________
> 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.
>
	[[alternative HTML version deleted]]

http://finzi.psych.upenn.edu/R/library/QuantPsyc/html/Make.Z.html

Make.Z in the QuantPsych package may already do it.

--- On Sun, 11/29/09, Karsten Wolf <wolf at uni-bremen.de> wrote:
> From: Karsten Wolf <wolf at uni-bremen.de>
> Subject: [R] How to z-standardize for subgroups?
> To: r-help at r-project.org
> Received: Sunday, November 29, 2009, 10:41 AM
> 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
> Universit?t Bremen - Fachbereich 12
> web: http://www.ifeb.uni-bremen.de/wolf/
> 
> ______________________________________________
> R-help at 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.
> 
__________________________________________________
Do You Yahoo!?
Tired of spam?

On 11/29/2009 4:23 PM, John Kane wrote:
> http://finzi.psych.upenn.edu/R/library/QuantPsyc/html/Make.Z.html
> 
> Make.Z in the QuantPsych package may already do it.
  For a single variable, you could use ave() and scale() together like this:

with(iris, ave(Sepal.Width, Species, FUN = scale))

  To scale more than one variable in a concise call, consider something
along these lines:

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

hope this helps,

Chuck Cleland
> --- On Sun, 11/29/09, Karsten Wolf <wolf at uni-bremen.de> wrote:
> 
>> From: Karsten Wolf <wolf at uni-bremen.de>
>> Subject: [R] How to z-standardize for subgroups?
>> To: r-help at r-project.org
>> Received: Sunday, November 29, 2009, 10:41 AM
>> 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
>> Universit?t Bremen - Fachbereich 12
>> web: http://www.ifeb.uni-bremen.de/wolf/
>>
>> ______________________________________________
>> R-help at 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.
>>
> 
> __________________________________________________
> Do You Yahoo!?
> Tired of spam?
> ______________________________________________
> R-help at 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.
-- 
Chuck Cleland, Ph.D.
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