[R] Problem with NA data when computing standard error
apcoble
coble.adam at gmail.com
Thu Apr 5 20:32:28 CEST 2012
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:*
object1<-as.data.frame.table(tapply(Data[Year=="1999"],na.rm=T,list(Group[Year=="1999"],Season[Year=="1999"]),mean))
object2<-as.data.frame.table(tapply(Data[Year=="1999"],na.rm=T,list(Group[Year=="1999"],Season[Year=="1999"]),se))
*Recommended code and round-about way to calculate se:*
1)
length.NA<-function(x)length(na.omit(x))
2)
object2.var<-as.data.frame.table(tapply(Data[Year=="1999"],na.rm=T,list(Group[Year=="1999"],Season[Year=="1999"]),var,na.rm=T))
3)
object2.length<-as.data.frame.table(tapply(Data[Year=="1999"],na.rm=T,list(Group[Year=="1999"],Season[Year=="1999"]),length.NA))
4)
sqrt(object2.var/object2.length)
This should give you SE for your parameters. For some reason, the revised
length function doesn't work when I created an SE function, but it worked
well when I calculated length.
--
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