Iterative sampling with restrictions

require(e1071)
groups <- apply(permutations(3), 1, function(x) paste(x, collapse="/"))
assign <- sample(rep(groups, 10))
table(assign)

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
project.org] On Behalf Of David L Carlson
Sent: Wednesday, August 22, 2012 5:11 PM
To: 'Daniel Nordlund'; r-help at r-project.org
Subject: Re: [R] Iterative sampling with restrictions

If I understand you, this is just random assignment over 6 groups: 1/2,
1/3,
2/1, 2/3, 3/1, 3/2.

groups <- c("1/2", "1/3", "2/1", "2/3", "3/1", "3/2")
assign <- sample(rep(groups, 10))
table(assign)

assign
1/2 1/3 2/1 2/3 3/1 3/2
 10  10  10  10  10  10

----------------------------------------------
David L Carlson
Associate Professor of Anthropology
Texas A&M University
College Station, TX 77843-4352

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
project.org] On Behalf Of Daniel Nordlund
Sent: Tuesday, August 21, 2012 2:58 AM
To: r-help at r-project.org
Subject: Re: [R] Iterative sampling with restrictions

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-

project.org]

On Behalf Of David A. Kim
Sent: Monday, August 20, 2012 9:17 PM
To: r-help at r-project.org
Subject: [R] Iterative sampling with restrictions

Hi all,

I'm working on a seemingly trivial problem that I can't figure out

how

to implement in R.  I'd be most grateful for any help here.

I want to do the following: first, randomly assign each of n units

to

one of g groups of size n/g. Then, randomly re-assign each of the n
units to a different group (i.e., same as the first step, but the

unit

can't be assigned to a group to which it's already belonged).  Then
repeat this step until each unit has at some point been assigned to
every group.

More concretely, say I have 60 units and 3 groups into which to

divide

the units.  I could first do something like:

group1<-sample(1:60,20)
group2<-sample(setdiff(1:60,group1),20)
group3<-sample(setdiff(1:60,c(group1,group2)),20)

But then how to randomly re-assign group membership such that all
units are assured a different group assignment in the second "wave"

of

grouping?  Just narrowing the sampling pool to those units that
weren't previously assigned to a given group won't work (consider

the

case where groups 1 and 2 swap units: in the second wave, there

would

be no units to assign to group 3 as all the remaining units had
already been in group 3 in the first wave).

Most grateful for any assistance,

David

David,

I would collect the sample waves into a data.frame.  I am sure

someone

will be able to help you with a more general and/or efficient

solution,

but to get you started I have provided one possible solution to your

60

unit 3 wave example

#create data.frame with IDs
df <- data.frame(id=1:60)

#create first sample wave
df$wave1 <- sample(rep(1:3,20))

#reorder df and create second wave sample
df <- df[order(df$wave1),]
df$wave2 <-  c(sample(rep(c(2,3),10)),
               sample(rep(c(1,3),10)),sample(rep(c(1,2),10)))

#now use set diff to create 3rd wave
for(i in 1:60) df[i,'wave3'] <- unlist(setdiff(1:3,df[i,2:3]))

df


Hope this is helpful,

Dan

Daniel Nordlund
Bothell, WA USA