From: Paul Johnson <pauljohn32_at_gmail.com>

Date: Tue, 08 Apr 2008 16:00:57 -0500

Date: Tue, 08 Apr 2008 16:00:57 -0500

On Tue, Apr 8, 2008 at 12:44 PM, LeCzar <sirnixu_at_gmail.com> wrote:

*>
**> Hey,
**>
*

> I want to compute means and standard errors as two tables like this:

*>
**> se<-function(x)sqrt(var(x)/length(x))
**>
**>
*

The missings are not your main problem.

The command var computes the variance-covariance matrix. Some covariance values can be negative. Trying to take square roots is a mistake.

For example, run

*> example(var)
*

to get some matrices to work with.

*> C1[3,4] <- NA
**> C1[3,5] <- NA
*

Observe you can calculate

*> var(C1, na.rm=T)
*

but you cannot take sqrt of that because it would try to apply sqrt to negative values.

To get the standard errors, it is necessary to reconsider the problem, do something like

*> diag(var(C1, na.rm=T))
*

That will give the diagonals, which are positive, so

*> sqrt(diag(var(C1, na.rm=T)))
*

Works as well.

But you have the separate problem of dividing each one by the square root of the length, and since there are missings that is not the same for every column. Maybe somebody knows a smarter way, but this appears to give the correct answer:

validX <- colSums( ! is.na(C1))

This gives the roots:

sqrt(validX)

Put that together, it seems to me you could try

se <- function(x) {

myDiag <- sqrt(diag(var(x, na.rm=T)))

validX <- colSums(! is.na(x))

myDiag/sqrt(validX)

}

That works for me:

*> se(C1)
*

Fertility Agriculture Examination Education 50.740226 110.808614 39.390611 39.303898 Catholic Infant.Mortality 328.272207 4.513863

-- Paul E. Johnson Professor, Political Science 1541 Lilac Lane, Room 504 University of Kansas ______________________________________________ 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.Received on Tue 08 Apr 2008 - 21:52:31 GMT

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