Hi Harold,

Many (most?) of the statistics function have a similar argument.  I
suspect it is sort of to warn the user---you have to be explicit about
it rather than the program just silently removing or ignoring values
that would not work in the function called.  I can think of one
example where I want a missing value returned.  In psychology we often
create scores on some construct (say optimism), by averaging
individuals' response to several questions.  In certain cases if a
subject does not respond to one question, their overall score should
be missing.  This is easily accomplished by letting na.rm = FALSE.

Cheers,

Josh

On Tue, Jul 12, 2011 at 9:26 AM, Doran, Harold <hdo...@air.org> wrote:
> This is just posed out of curiosity, (not as a criticism per se). But what is 
> the functional role of the argument na.rm inside the mean() function? If 
> there are missing values, mean() will always return an NA as in the example 
> below. But, is there ever a purpose in computing a mean only to receive NA as 
> a result?
>
> In 10 years of using R, I have always used mean() in order to get a result, 
> which is the opposite of its default behavior (when there are NAs). Can 
> anyone suggest a reason why it is in fact desired to get NA as a result of 
> computing mean()?
>
>> x <- rnorm(100)
>> x[1] <- NA
>
>> mean(x)
> [1] NA
>
>> mean(x, na.rm=TRUE)
> [1] 0.08136736
>
> If the reason is to alert the user that the vector has missing values, I 
> suppose I could buy that. But, I think other checks are better
>
> Harold
>
>
>        [[alternative HTML version deleted]]
>
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-- 
Joshua Wiley
Ph.D. Student, Health Psychology
University of California, Los Angeles
https://joshuawiley.com/

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