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Richardson, Patrick

2009-Aug-27 23:37 UTC

[R] Transform data for repeated measures

I have a dataset that I'm trying to rearrange for a repeated measures
analysis:

It looks like:

patient basefev1 fev11h fev12h fev13h fev14h fev15h fev16h fev17h fev18h drug
201     2.46   2.68   2.76   2.50   2.30   2.14   2.40   2.33   2.20    a
202     3.50   3.95   3.65   2.93   2.53   3.04   3.37   3.14   2.62    a
203     1.96   2.28   2.34   2.29   2.43   2.06   2.18   2.28   2.29    a
204     3.44   4.08   3.87   3.79   3.30   3.80   3.24   2.98   2.91    a

And I want to make it look like:

Patient  FEV  time  drug
201         2.46    0         a
201         2.68    1         a
201         2.76    2         a
201         2.50    3         a

And so on . . . . . There would be 9 "time" and drug is a factor
variable.

I know there is a way to do this in R but I cannot remember the function.
I've looked at the transpose function in (base) but that doesn't seem to
be what I want. Can something like this be done easily from within package
functions or would it require writing something custom? Another program would
use something like the transpose procedure, but I'm trying to stay away from
that program.

Thanks,

Patrick

R version 2.9.2 (2009-08-24) 
i386-pc-mingw32 

locale:
LC_COLLATE=English_United States.1252;LC_CTYPE=English_United
States.1252;LC_MONETARY=English_United
States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252

attached base packages:
[1] grDevices datasets  tcltk     splines   graphics  stats     utils    
methods   base

other attached packages:
[1] svSocket_0.9-43 svMisc_0.9.48   TinnR_1.0.3     R2HTML_1.59-1   Hmisc_3.6-1 
survival_2.35-4

loaded via a namespace (and not attached):
[1] cluster_1.12.0  grid_2.9.2      lattice_0.17-25 tools_2.9.2
This email message, including any attachments, is for th...{{dropped:6}}

Rolf Turner

2009-Aug-27 23:46 UTC

head link

[R] Transform data for repeated measures

?reshape

On 28/08/2009, at 11:37 AM, Richardson, Patrick wrote:
> I have a dataset that I'm trying to rearrange for a repeated  
> measures analysis:
>
> It looks like:
>
> patient basefev1 fev11h fev12h fev13h fev14h fev15h fev16h fev17h  
> fev18h drug
> 201     2.46   2.68   2.76   2.50   2.30   2.14   2.40   2.33    
> 2.20    a
> 202     3.50   3.95   3.65   2.93   2.53   3.04   3.37   3.14    
> 2.62    a
> 203     1.96   2.28   2.34   2.29   2.43   2.06   2.18   2.28    
> 2.29    a
> 204     3.44   4.08   3.87   3.79   3.30   3.80   3.24   2.98    
> 2.91    a
>
> And I want to make it look like:
>
> Patient  FEV  time  drug
> 201         2.46    0         a
> 201         2.68    1         a
> 201         2.76    2         a
> 201         2.50    3         a
>
> And so on . . . . . There would be 9 "time" and drug is a factor
> variable.
>
> I know there is a way to do this in R but I cannot remember the  
> function. I've looked at the transpose function in (base) but that  
> doesn't seem to be what I want. Can something like this be done  
> easily from within package functions or would it require writing  
> something custom? Another program would use something like the  
> transpose procedure, but I'm trying to stay away from that program.
>
> Thanks,
>
> Patrick
######################################################################
Attention:\ This e-mail message is privileged and confid...{{dropped:9}}

Bert Gunter

2009-Aug-27 23:51 UTC

head link

[R] Transform data for repeated measures

I suspect reshape() is the function you're looking for; there is also a
reshape package that you might prefer.

It's also quite easy to do this in base R using unlist() and some indexing
with rep, but that may be more than you care to deal with.

Bert Gunter
Genentech Nonclinical Biostatisics

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On
Behalf Of Richardson, Patrick
Sent: Thursday, August 27, 2009 4:37 PM
To: r help
Subject: [R] Transform data for repeated measures

I have a dataset that I'm trying to rearrange for a repeated measures
analysis:

It looks like:

patient basefev1 fev11h fev12h fev13h fev14h fev15h fev16h fev17h fev18h
drug
201     2.46   2.68   2.76   2.50   2.30   2.14   2.40   2.33   2.20    a
202     3.50   3.95   3.65   2.93   2.53   3.04   3.37   3.14   2.62    a
203     1.96   2.28   2.34   2.29   2.43   2.06   2.18   2.28   2.29    a
204     3.44   4.08   3.87   3.79   3.30   3.80   3.24   2.98   2.91    a

And I want to make it look like:

Patient  FEV  time  drug
201         2.46    0         a
201         2.68    1         a
201         2.76    2         a
201         2.50    3         a

And so on . . . . . There would be 9 "time" and drug is a factor
variable.

I know there is a way to do this in R but I cannot remember the function.
I've looked at the transpose function in (base) but that doesn't seem to
be
what I want. Can something like this be done easily from within package
functions or would it require writing something custom? Another program
would use something like the transpose procedure, but I'm trying to stay
away from that program.

Thanks,

Patrick

R version 2.9.2 (2009-08-24) 
i386-pc-mingw32 

locale:
LC_COLLATE=English_United States.1252;LC_CTYPE=English_United
States.1252;LC_MONETARY=English_United
States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252

attached base packages:
[1] grDevices datasets  tcltk     splines   graphics  stats     utils
methods   base     

other attached packages:
[1] svSocket_0.9-43 svMisc_0.9.48   TinnR_1.0.3     R2HTML_1.59-1
Hmisc_3.6-1     survival_2.35-4

loaded via a namespace (and not attached):
[1] cluster_1.12.0  grid_2.9.2      lattice_0.17-25 tools_2.9.2
This email message, including any attachments, is for th...{{dropped:8}}

David Winsemius

2009-Aug-28 15:13 UTC

head link

[R] Transform data for repeated measures

Patrick;

You got two helpful suggestions for where to start your learning how  
to reshape your data. I am going to admit that I have recurring  
difficulty using either reshape() or the functions in the reshape  
package. It undoubtedly reflects some sort of "constricted abstraction  
capability" on my part, but I have learned that sometimes I get what I  
need from a combination of rep() and the stack() function. The  
strategy is to rep() the recurring variables and stack() the repeated  
measures on the same subjects

  resp.df <- read.table(textConnection("patient basefev1 fev11h fev12h  
fev13h fev14h fev15h fev16h fev17h fev18h drug
  201     2.46   2.68   2.76   2.50   2.30   2.14   2.40   2.33    
2.20    a
  202     3.50   3.95   3.65   2.93   2.53   3.04   3.37   3.14    
2.62    a
  203     1.96   2.28   2.34   2.29   2.43   2.06   2.18   2.28    
2.29    a
  204     3.44   4.08   3.87   3.79   3.30   3.80   3.24   2.98    
2.91    a"), header=TRUE)
closeAllConnections()

  stk.resp <- data.frame(pt.id.=rep(resp.df$patient, 9), FEV1  
=stack(resp.df[,2:10]), drug=rep(resp.df$drug, 9))

  stk.resp

    pt.id. FEV1.values FEV1.ind drug
1     201        2.46 basefev1    a
2     202        3.50 basefev1    a
3     203        1.96 basefev1    a
4     204        3.44 basefev1    a
5     201        2.68   fev11h    a
6     202        3.95   fev11h    a
7     203        2.28   fev11h    a
8     204        4.08   fev11h    a
snipped further unneeded output

HTH;
David.


On Aug 27, 2009, at 7:37 PM, Richardson, Patrick wrote:
> I have a dataset that I'm trying to rearrange for a repeated  
> measures analysis:
>
> It looks like:
>
> patient basefev1 fev11h fev12h fev13h fev14h fev15h fev16h fev17h  
> fev18h drug
> 201     2.46   2.68   2.76   2.50   2.30   2.14   2.40   2.33    
> 2.20    a
> 202     3.50   3.95   3.65   2.93   2.53   3.04   3.37   3.14    
> 2.62    a
> 203     1.96   2.28   2.34   2.29   2.43   2.06   2.18   2.28    
> 2.29    a
> 204     3.44   4.08   3.87   3.79   3.30   3.80   3.24   2.98    
> 2.91    a
>
> And I want to make it look like:
>
> Patient  FEV  time  drug
> 201         2.46    0         a
> 201         2.68    1         a
> 201         2.76    2         a
> 201         2.50    3         a
>
> And so on . . . . . There would be 9 "time" and drug is a factor
> variable.
>
> I know there is a way to do this in R but I cannot remember the  
> function. I've looked at the transpose function in (base) but that  
> doesn't seem to be what I want. Can something like this be done  
> easily from within package functions or would it require writing  
> something custom? Another program would use something like the  
> transpose procedure, but I'm trying to stay away from that program.
>
> Thanks,
>
> Patrick
David Winsemius, MD
Heritage Laboratories
West Hartford, CT

Henrique Dallazuanna

2009-Aug-28 16:21 UTC

head link

[R] Transform data for repeated measures

Using reshape you can try this:

reshape(resp.df, direction = "long", idvar="patient",
varying list(grep("fev", names(resp.df))))

On Thu, Aug 27, 2009 at 8:37 PM, Richardson, Patrick <
Patrick.Richardson@vai.org> wrote:
> I have a dataset that I'm trying to rearrange for a repeated measures
> analysis:
>
> It looks like:
>
> patient basefev1 fev11h fev12h fev13h fev14h fev15h fev16h fev17h fev18h
> drug
> 201     2.46   2.68   2.76   2.50   2.30   2.14   2.40   2.33   2.20    a
> 202     3.50   3.95   3.65   2.93   2.53   3.04   3.37   3.14   2.62    a
> 203     1.96   2.28   2.34   2.29   2.43   2.06   2.18   2.28   2.29    a
> 204     3.44   4.08   3.87   3.79   3.30   3.80   3.24   2.98   2.91    a
>
> And I want to make it look like:
>
> Patient  FEV  time  drug
> 201         2.46    0         a
> 201         2.68    1         a
> 201         2.76    2         a
> 201         2.50    3         a
>
> And so on . . . . . There would be 9 "time" and drug is a factor
variable.
>
> I know there is a way to do this in R but I cannot remember the function.
> I've looked at the transpose function in (base) but that doesn't
seem to be
> what I want. Can something like this be done easily from within package
> functions or would it require writing something custom? Another program
> would use something like the transpose procedure, but I'm trying to
stay
> away from that program.
>
> Thanks,
>
> Patrick
>
> R version 2.9.2 (2009-08-24)
> i386-pc-mingw32
>
> locale:
> LC_COLLATE=English_United States.1252;LC_CTYPE=English_United
> States.1252;LC_MONETARY=English_United
> States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252
>
> attached base packages:
> [1] grDevices datasets  tcltk     splines   graphics  stats     utils
> methods   base
>
> other attached packages:
> [1] svSocket_0.9-43 svMisc_0.9.48   TinnR_1.0.3     R2HTML_1.59-1
> Hmisc_3.6-1     survival_2.35-4
>
> loaded via a namespace (and not attached):
> [1] cluster_1.12.0  grid_2.9.2      lattice_0.17-25 tools_2.9.2
> This email message, including any attachments, is for ...{{dropped:20}}

hadley wickham

2009-Aug-28 17:13 UTC

head link

[R] Transform data for repeated measures

On Thu, Aug 27, 2009 at 6:37 PM, Richardson,
Patrick<Patrick.Richardson at vai.org> wrote:> I have a dataset that I'm trying to rearrange for a repeated measures
analysis:
>
> It looks like:
>
> patient basefev1 fev11h fev12h fev13h fev14h fev15h fev16h fev17h fev18h
drug
> 201 ? ? 2.46 ? 2.68 ? 2.76 ? 2.50 ? 2.30 ? 2.14 ? 2.40 ? 2.33 ? 2.20 ? ?a
> 202 ? ? 3.50 ? 3.95 ? 3.65 ? 2.93 ? 2.53 ? 3.04 ? 3.37 ? 3.14 ? 2.62 ? ?a
> 203 ? ? 1.96 ? 2.28 ? 2.34 ? 2.29 ? 2.43 ? 2.06 ? 2.18 ? 2.28 ? 2.29 ? ?a
> 204 ? ? 3.44 ? 4.08 ? 3.87 ? 3.79 ? 3.30 ? 3.80 ? 3.24 ? 2.98 ? 2.91 ? ?a
>
> And I want to make it look like:
>
> Patient ?FEV ?time ?drug
> 201 ? ? ? ? 2.46 ? ?0 ? ? ? ? a
> 201 ? ? ? ? 2.68 ? ?1 ? ? ? ? a
> 201 ? ? ? ? 2.76 ? ?2 ? ? ? ? a
> 201 ? ? ? ? 2.50 ? ?3 ? ? ? ? a
>
> And so on . . . . . There would be 9 "time" and drug is a factor
variable.
>
> I know there is a way to do this in R but I cannot remember the function.
I've looked at the transpose function in (base) but that doesn't seem to
be what I want. Can something like this be done easily from within package
functions or would it require writing something custom? Another program would
use something like the transpose procedure, but I'm trying to stay away from
that program.
To give a concrete example of what using the reshape package would
look like: (thanks to David for making your example easily
reproducible)

 resp.df <- read.table(textConnection("patient basefev1 fev11h fev12h
fev13h fev14h fev15h fev16h fev17h fev18h drug

 201     2.46   2.68   2.76   2.50   2.30   2.14   2.40   2.33   2.20    a
 202     3.50   3.95   3.65   2.93   2.53   3.04   3.37   3.14   2.62    a
 203     1.96   2.28   2.34   2.29   2.43   2.06   2.18   2.28   2.29    a
 204     3.44   4.08   3.87   3.79   3.30   3.80   3.24   2.98   2.91
  a"), header=TRUE)
closeAllConnections()

library(reshape)
# Identify the variables controlled by your experimental design:
stk.resp <- melt(resp.df, id = c("patient", "drug"))
stk.resp$time <- as.numeric(gsub("[^0-9]", "",
stk.resp$variable))

Hadley

-- 
http://had.co.nz/

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