Re: [R] Problem with NA data when computing standard error

I found a rather easy solution that circumvents this problem by: 1) creating your own length function using na.omit function 2) calculating variance using tapply 3) calculating length using new length function 4) calculating square root of variance by length *Code from LeCzar:*

[R] Problem with NA data when computing standard error

Hey, I want to compute means and standard errors as two tables like this: se-function(x)sqrt(var(x)/length(x)) object1-as.data.frame.table(tapply(Data[Year==1999],na.rm=T,list(Group[Year==1999],Season[Year==1999]),mean))

Re: [R] Problem with NA data when computing standard error

Hi there, Perhaps se-function(x)sqrt(var(x,na.rm=T)/sum(!is.na(x))) object1-as.data.frame.table(tapply(Data[Year==1999],list(Group[Year==1999],Season[Year==1999]),mean)) object2-as.data.frame.table(tapply(Data[Year==1999],list(Group[Year==1999],Season[Year==1999]),se)) Hope this helps, Jorge

Re: [R] Problem with NA data when computing standard error

On Tue, Apr 8, 2008 at 12:44 PM, LeCzar [EMAIL PROTECTED] 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