[R] randomly sample within clustered data?

[Brown, Tony Nicholas]

Thierry,

Thanks so much. Your solution works perfectly.

Tony

-----Original Message-----
From: ONKELINX, Thierry [mailto:Thierry.ONKELINX at inbo.be] 
Sent: Monday, September 15, 2008 2:56 AM
To: Brown, Tony Nicholas; r-help at r-project.org
Subject: RE: [R] randomly sample within clustered data?

Something like this?

do.call("rbind", 
	lapply(
		split(Dataf, Dataf$id), 
		function(x){
			x[sample(seq_len(nrow(x)), size=2), ]
		}
	)
)
 
HTH,

Thierry

------------------------------------------------------------------------
----
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature
and Forest
Cel biometrie, methodologie en kwaliteitszorg / Section biometrics,
methodology and quality assurance
Gaverstraat 4
9500 Geraardsbergen
Belgium 
tel. + 32 54/436 185
Thierry.Onkelinx at inbo.be 
www.inbo.be 

To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to
say what the experiment died of.
~ Sir Ronald Aylmer Fisher

The plural of anecdote is not data.
~ Roger Brinner

The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of
data.
~ John Tukey

-----Oorspronkelijk bericht-----
Van: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
Namens Brown, Tony Nicholas
Verzonden: maandag 15 september 2008 9:40
Aan: r-help at r-project.org
Onderwerp: [R] randomly sample within clustered data?

Dear useRs,



What is an efficient way to randomly sample from clustered data such
that I get equal representation from each cluster? For example, let's
say I want to randomly sample two cases from each cluster created by the
"id" variable in the following data frame:



> id<-c(rep("100", 4),rep("101", 3), rep("102", 6), rep("103", 7))

> sex<-sample(c("m","f"), 20, replace=TRUE)

> weight<-rnorm(n=20, mean=150, sd=3)

> attitude<-sample(1:7, 20, replace=TRUE)

> Dataf<-data.frame(id,sex,weight,attitude)

> Dataf

    id sex   weight attitude

1  100   m 146.5064        6

2  100   f 150.2317        4

3  100   f 149.3686        5

4  100   m 144.7218        7

5  101   m 147.9071        4

6  101   m 148.3802        6

7  101   m 154.4634        1

8  102   m 153.2719        5

9  102   m 148.9821        5

10 102   f 148.0656        1

11 102   f 148.8949        6

12 102   m 146.9963        4

13 102   m 153.0542        4

14 103   m 148.1558        1

15 103   f 148.0482        4

16 103   m 151.8044        2

17 103   f 155.4976        4

18 103   m 150.0423        1

19 103   f 146.0487        5

20 103   m 154.6651        7

> 



Here's the R code I wrote that obviously does not work:



sapply(split(Dataf, Dataf$id), sample, size=2)



I would prefer a data frame (i.e., Dataf2) as the final output and it
should look something like this:



> Dataf2

    id sex   weight attitude

1  100   m 146.5064        6

2  100   m 144.7218        7

3  101   m 147.9071        4

4  101   m 154.4634        1

5  102   m 153.2719        5

6  102   m 148.9821        5

7  103   f 155.4976        4

8  103   f 146.0487        5

> 



Thanks in advance in your assistance.



Tony





------------------------------------------------------------------



Tony N. Brown, Ph.D.

Associate Professor of Sociology

Faculty Head of Hank Ingram House, The Commons

Research Fellow, Vanderbilt Center for Nashville Studies

Vanderbilt University

(615) 322-7518

(615) 322-7505 fax

tony.n.brown at vanderbilt.edu <mailto:tony.n.brown at vanderbilt.edu> 




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