Thank you all for the responses, these are the insights I was hoping for.
There are many ways to get this right, and I happened to run into one that
has a glitch. I see from Luke's explanation how the strange output came
about. Glad to hear that this bug/behavior is already known.
On Fri, Jun 19, 2020 at 7:04 PM Daniel Nordlund
wrote:
> On 6/19/2020 5:49 AM, Sébastien Lahaie wrote:
> > I ran into some strange behavior in R when trying to assign a treatment
> to
> > rows in a data frame. I'm wondering whether any R experts can explain
> > what's going on.
> >
> > First, let's assign a treatment to 3 out of 10 rows as follows.
> >
> > df <- data.frame(unit = 1:10)
> > df$treated <- FALSE
> > s <- sample(nrow(df), 3)
> > df[s,]$treated <- TRUE
> > df
> > unit treated
> > 1 1 FALSE
> > 2 2TRUE
> > 3 3 FALSE
> > 4 4 FALSE
> > 5 5TRUE
> > 6 6 FALSE
> > 7 7TRUE
> > 8 8 FALSE
> > 9 9 FALSE
> > 10 10 FALSE
> >
> > This is as expected. Now we'll just skip the intermediate step of saving
> > the sampled indices, and apply the treatment directly as follows.
> >
> > df <- data.frame(unit = 1:10)
> > df$treated <- FALSE
> > df[sample(nrow(df), 3),]$treated <- TRUE
> > df
> > unit treated
> > 1 6TRUE
> > 2 2 FALSE
> > 3 3 FALSE
> > 4 9TRUE
> > 5 5 FALSE
> > 6 6 FALSE
> > 7 7 FALSE
> > 8 5TRUE
> > 9 9 FALSE
> > 10 10 FALSE
> >
> > Now the data frame still has 10 rows with 3 assigned to the treatment.
> But
> > the units are garbled. Units 1 and 4 have disappeared, for instance, and
> > there are duplicates for 6 and 9, one assigned to treatment and the other
> > to control. Why would this happen?
> >
> > Thanks,
> > Sebastien
> >
> Sébastien,
>
> You have received good explanations of what is going on with your code.
> I think you can get what you want by making a simple modification of
> your treatment assignment statement. At least it works for me.
>
> df[sample(nrow(df),3), 'treated'] <- TRUE
>
> Hope this is helpful,
>
> Dan
>
> --
> Daniel Nordlund
> Port Townsend, WA USA
>
>
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