[R] assigning creating missing rows and values

[Adele_Thompson at cargill.com]

I am still working on the weights problem. If the animals do not eat (like after sunset), then no new feed weight will be calculated and no new row will be entered. Thus, if I just use the previous value, it should be correct for how much cumulative feed was eaten that day up to that point.
I will play around with that package and try getting it to work for me. Thank you.

-----Original Message-----
From: gunter.berton at gene.com [mailto:gunter.berton at gene.com] 
Sent: Thursday, May 12, 2011 04:13 PM
To: dwinsemius at comcast.net
Cc: Thompson, Adele - Adele_Thompson at cargill.com; r-help at r-project.org
Subject: Re: [R] assigning creating missing rows and values

...  But beware: Last observation carried forward is a widely used but
notoriously bad (biased) way to impute missing values; and, of course,
inference based on such single imputation is bogus (how bogus depends
on how much imputation, among other things, of course).
Unfortunately, dealing with such data "well" requires considerable
statistical sophistication, which is why statisticians are widely
employed in the clinical trial business, where missing data in
longitudinal series are relatively common. You may therefore find it
useful to consult a local statistician if one is available.

As an extreme -- and unrealistic -- example of the problem,  suppose
your series consisted of 12 hours of data measured every half hour and
that one series had only two measurements, the first and the last. The
first value is 10 and the last is 1. LOCF would fill in the missings
as all 10's. Obviously, a dumb thing to do. For real data, the problem
would  not be so egregious, but the fundamental difficulty is the
same.

(Apologies to those for whom my post is a familiar, boring refrain.
Unfortunately, I do not have the imagination to offer better).

Cheers,
Bert

On Thu, May 12, 2011 at 1:43 PM, David Winsemius <dwinsemius at comcast.net> wrote:
>
> On May 12, 2011, at 4:33 PM, Schatzi wrote:
>
>> I have a dataset where I have missing times (11:00 and 16:00). I would
>> like
>> the outputs to include the missing time so that the final time vector
>> looks
>> like "realt" and has the previous time's value. Ex. If meas at time 15:30
>> is
>> 0.45, then the meas for time 16:00 will also be 0.45.
>> meas are the measurements and times are the times at which they were
>> taken.
>>
>> meas<-runif(18)
>>
>> times<-c("08:30","09:00","09:30","10:00","10:30","11:30","12:00","12:30","13:00","13:30","14:00","14:30","15:00",
>> "15:30" ,"16:30","17:00","17:30","18:00")
>> output<-data.frame(meas,times)
>>
>> realt<-c("08:30","09:00","09:30","10:00","10:30","11:00","11:30","12:00","12:30","13:00","13:30","14:00","14:30","15:00","15:30","16:00","16:30","17:00","17:30","18:00")
>
> Package 'zoo' has an 'na.locf' function which I believe stands for "NA's
> last observation carried forward". So make a regular set of times, merge and
> "carry forward". I'm pretty sure you can find may examples in the Archive.
> Gabor is very good about spotting places where his many contributions can be
> successfully deployed.
>
> --
>
> David Winsemius, MD
> West Hartford, CT
>
> ______________________________________________
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>



-- 
"Men by nature long to get on to the ultimate truths, and will often
be impatient with elementary studies or fight shy of them. If it were
possible to reach the ultimate truths without the elementary studies
usually prefixed to them, these would not be preparatory studies but
superfluous diversions."

-- Maimonides (1135-1204)

Bert Gunter
Genentech Nonclinical Biostatistics