R help - Apr 2014 - Within ID variable delete all rows after reaching a specific value

So, I know that's a confusing Subject header.

Here's similar data:


tmp <- data.frame(matrix(
                        c(rbinom(1000, 1, .03),
                          array(1:127, c(1000,1)),
                          array(format(seq(ISOdate(1990,1,1),
by='month',
length=56), format='%d.%m.%Y'), c(1000,1))),
                        ncol=3))
tmp <- tmp[with(tmp, order(X2, X3)), ]
table(tmp$X1)


X1 is the variable of interest - disease status.  It's a survival-type of
variable, where you are 0 until you become 1.
X2 is the person ID variable.
X3 is the clinic date (here it's monthly, just for example...but in my real
data it's a bit more complicated - definitely not equally spaced nor the
same number of visits to the clinic per ID.).

Some people stay X1 = 0 for all clinic visits.  Only a small proportion
become X1=1.

However, the data has errors I need to clean off.  Once someone becomes
X1=1 they should have no more rows in the dataset.  These are data entry
errors.

In my data I have people who continue to have rows in the data.  Sometimes
the rows show X1=0 and sometimes X1=1.  Sometimes there's just one more row
and sometimes there are many more rows.

How can I go through, find the first X1 = 1, and then delete any rows after
that, for each value of X2?

Thanks!

Jen

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On 04/26/2014 12:42 PM, Jennifer Sabatier wrote:
> So, I know that's a confusing Subject header.
>
> Here's similar data:
>
>
> tmp<- data.frame(matrix(
>                          c(rbinom(1000, 1, .03),
>                            array(1:127, c(1000,1)),
>                            array(format(seq(ISOdate(1990,1,1),
by='month',
> length=56), format='%d.%m.%Y'), c(1000,1))),
>                          ncol=3))
> tmp<- tmp[with(tmp, order(X2, X3)), ]
> table(tmp$X1)
>
>
> X1 is the variable of interest - disease status.  It's a survival-type
of
> variable, where you are 0 until you become 1.
> X2 is the person ID variable.
> X3 is the clinic date (here it's monthly, just for example...but in my
real
> data it's a bit more complicated - definitely not equally spaced nor
the
> same number of visits to the clinic per ID.).
>
> Some people stay X1 = 0 for all clinic visits.  Only a small proportion
> become X1=1.
>
> However, the data has errors I need to clean off.  Once someone becomes
> X1=1 they should have no more rows in the dataset.  These are data entry
> errors.
>
> In my data I have people who continue to have rows in the data.  Sometimes
> the rows show X1=0 and sometimes X1=1.  Sometimes there's just one more
row
> and sometimes there are many more rows.
>
> How can I go through, find the first X1 = 1, and then delete any rows after
> that, for each value of X2?
>
> Thanks!
>
> Jen
>
Hi Jen,
This might do what you want:

tmp$X3<-as.Date(tmp$X3,"%d.%m.%Y")
tmp<-tmp[order(tmp$X2,tmp$X3),]
first<-TRUE
for(patno in unique(tmp$X2)) {
  cat(patno,"\n")
  tmpbit<-tmp[tmp$X2 == patno,]
  firstone<-which(tmpbit$X1 == 1)[1]
  cat(firstone,"\n")
  if(is.na(firstone)) firstone<-dim(tmpbit)[1]
  newtmpbit<-tmpbit[1:firstone,]
  if(first) {
   newtmp<-newtmpbit
   first<-FALSE
  }
  else newtmp<-rbind(newtmp,newtmpbit)
}

Jim