[R] How to ignore data
sbsidney at mweb.co.za
Mon Dec 13 18:42:47 CET 2010
Thanks for the questions.
1) The data represents micro-organism counts and a count of zero in
this case is highly unlikely given the info we have; including the other
2) The data is submitted in duplicate and then a standardised sum and
difference is established and is used to calculate a Z-score which is
used as a measure of performance.
Given both 1) and 2) it is necessary to exclude a raw count of zero
(since the log of 0 is meaningless) and a count of one (since the log of
1 of course is zero).
I guess one can think of these values as outliers and that is what I am
trying to exclude.
There is ample evidence that such an approach is acceptable.
Thanks for the interest
On 2010/12/13 06:47 PM, Stavros Macrakis wrote:
> If you need to take the log of the values for your calculation, then
> what does it mean that you have 0 values in the input?
> And why do you need to exclude the 1 values?
> Are you sure that a) you are doing the correct kind of analysis and b)
> the analysis is correct if you exclude 0 and 1?
> On Mon, Dec 13, 2010 at 10:38, Steve Sidney<sbsidney at mweb.co.za> wrote:
>> Dear list
>> I have quite a small data set in which I need to have the following values
>> ignored - not used when performing an analysis but they need to be included
>> later in the report that I write.
>> Can anyone help with a suggestion as to how this can be accomplished
>> Values to be ignored
>> 0 - zero and 1 this is in addition to NA (null)
>> The reason is that I need to use the log10 of the values when performing the
>> Currently I hand massage the data set, about a 100 values, of which less
>> than 5 to 10 are in this category.
>> The NA values are NOT the problem
>> What I was hoping was that I did not have to use a series of if and ifelse
>> statements. Perhaps there is a more elegant solution.
>> Any ideas would be welcomed.
>> R-help at r-project.org mailing list
>> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
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