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){
retu
N = 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$Species, FUN = scale)})
hope this helps,
Chuck Cleland
> --- On Sun, 11/29/09, Karsten Wolf wrote:
>
>> From: Karsten Wolf
>> Subjec
http://finzi.psych.upenn.edu/R/library/QuantPsyc/html/Make.Z.html
Make.Z in the QuantPsych package may already do it.
--- On Sun, 11/29/09, Karsten Wolf wrote:
> From: Karsten Wolf
> Subject: [R] How to z-standardize for subgroups?
> To: r-help@r-project.org
> Received: Sunday,
Hi Karsten,
Let me assume your data is called d. If I understood what you are trying to
do, the following might help:
res <- apply(d, 2, tapply, d$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 f
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(dat
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