Hi AK
That works. I was trying to get similar results from any other package.
Being a beginner, I was not sure how to modify the syntax to get my output.
lapply(split(BP_2bSexNoMV,BP_
2bSexNoMV$Sex),function(x) (nrow(x[!complete.cases(x[,-2]),])/nrow(x))*100)
#gives the percentage of rows of missing #values from the overall rows for
Males and Females
#$Female
#[1] 72.65522
#
#$Male
#[1] 74.47401
#iF you want the percentage from the total number rows in Males and Females
(without NA's in the the Sex column)
lapply(split(BP_2bSexNoMV,BP_2bSexNoMV$Sex),function(x)
(nrow(x[!complete.cases(x[,-2]),])/nrow(BP_2bSexNoMV))*100)
#$Female
#[1] 35.14377
#
#$Male
#[1] 38.45048
How do I interpret the above 2 difft results? 72.66% of values were missing
among female participants?? Can you pl. clarify.
Many thanks.
On Sun, Jan 13, 2013 at 3:28 AM, arun <smartpink...@yahoo.com> wrote:
> lapply(split(BP_2bSexNoMV,BP_2bSexNoMV$Sex),function(x)
> (nrow(x[!complete.cases(x[,-2]),])/nrow(x))*100) #gives the percentage of
> rows of missing #values from the overall rows for Males and Females
> #$Female
> #[1] 72.65522
> #
> #$Male
> #[1] 74.47401
>
> #iF you want the percentage from the total number rows in Males and
> Females (without NA's in the the Sex column)
> lapply(split(BP_2bSexNoMV,BP_2bSexNoMV$Sex),function(x)
> (nrow(x[!complete.cases(x[,-2]),])/nrow(BP_2bSexNoMV))*100)
> #$Female
> #[1] 35.14377
> #
> #$Male
> #[1] 38.45048
>
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