Hello, I'm trying to take a PPS systematic sample of a data set, and I've
gotten stuck at the last point. I have selection numbers, and just need to
pick out the units whose cumulative size are the least upper bounds of
these numbers
This is as close as I've gotten:
selected<-array(dim=c(97,4))
Hello,
I have a data set with many individuals all with multiple timed
observations, and I would like to subset the data to exclude later timed
observations.
However, I would like to exclude different amounts of data for each
individual. These individuals have two types of data: DV and dose. What
Hello,
I am branching out to xyplot for the first time, and I want to layer
several "complex" xyplots. I have tried using panel functions, but so far I
lose all complexity from the scatterplot. I would like to have the
following things in the plot:
1) A plot of observation vs. modeled individual
Yes, except that patients have different cycle numbers. Such as, one might
have cycle 1,2,3, and another has 1,4,12.
On Jun 6, 2012 12:54 PM, "arun" wrote:
> Hi Iglucia,
>
> I am not sure how your dataset looks like. Does it look similar to this:
>
> > dat4<-data.frame(patient=rep(c(1:10),
> rep
NA 0.3861208 1.1349206
> 99 1.5659958 1.8725942 1.5676570
> 10 10 1.0895054 1.1941775 1.3932515
>
>
> For the missing values, I assume that cycle will be in the dataset on the
> longformat and its value as NA.
>
>
> A.K.
>
>
> ___
Hello, I have a data set where there are multiple "cycles" per "patient,"
and I want to exclude from my data set instances where a variable was not
measured every cycle. The difficulty is that the patients have different
cycles; some have cycles 1,2, and 3, others only have 1 and 3 (and
everything
Hello, I need to subset my data to only look at the parts that have "holes"
in it. I already have a formula to get rid of inconsistencies, but now I
need to look only at the problem data to reconfigure it. In my data set
where there are multiple "cycles" per "patient," and I want to highlight
the p
Hello,
I didn't give enough information when I sent an query before, so I'm trying
again with a more detailed explanation:
In this data set, each patient has a different number of measured variables
(they represent tumors, so some people had 2 tumors, some had 5, etc). The
problem I have is that
rote:
> Hello,
>
> I guess so, and I can save you some typing.
>
> vars <- sort(apply(expand.grid("L", 1:8, 1:2), 1, paste, collapse=""))
>
>
> Then use it and see the result.
>
> Rui Barradas
>
> Em 20-07-2012 00:00, Lib Gray escreveu
e without a dataset to
> test it.
>
> Try
>
> pattern <- "L[1-8][12]"
>
> and after the grep print nms to see if it's right.
>
> Rui Barradas
>
> Em 20-07-2012 00:33, Lib Gray escreveu:
>
>> I'm getting this error message:
>>
>> nms
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