[R] assigning creating missing rows and values

Fri May 13 18:01:36 CEST 2011

The problem with using cumsum, is that the measured output is the cumulative feed consumed throughout the day. When the animals do not eat for 30 minutes or so, it will not output a new value, but as soon as they do eat, the scale will weigh the difference and then output the cumulative feed eaten that day. I can take the difference at each weighing so the numbers are the amount eaten at that feeding time, and then go back and use cumsum, but that seems a bit round about.

-----Original Message-----
From: gunter.berton at gene.com [mailto:gunter.berton at gene.com] 
Sent: Thursday, May 12, 2011 05:49 PM
To: Thompson, Adele - Adele_Thompson at cargill.com
Cc: dwinsemius at comcast.net
Subject: Re: [R] assigning creating missing rows and values

... Your detailed subject matter knowledge is always more relevant
than my general statistical comments.

If you are recording something like total cumulative input and the
missing values must be 0 input, you may wish to consider entering them
as 0 and then using the cumsum() function on the vector of inputs to
produce the cumulative totals for all times. Depending on your data,
code that might do this is:

data:

time  = ordered vector of times at which you have data
y = vector of (unaccumulated) input values, of same length as time
alltimes = complete ordered vector of all times

code: (untested)

new.y <- rep(0,length(alltimes))
new.y[match(time,alltimes)] <- y
cumsum(new.y)  ## is your answer

Note also that if y is a vector of your cumulative inputs,
c(y[1],diff(y))  is a vector of the unaccumulated inputs.

There, of course, many slicker ways to do this depending on your the
form of your data.

Cheers,
Bert

But I may misunderstand your issues ...

Cheers,
Bert

On Thu, May 12, 2011 at 2:26 PM,  <Adele_Thompson at cargill.com> wrote:
> 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
>>
>> ______________________________________________
>> R-help at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-help
>> 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
>

-- 
"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
467-7374
http://devo.gene.com/groups/devo/depts/ncb/home.shtml