Perhaps this would work:
spitzSum <- function(x) if(all(is.na(x))) NA else sum(x, na.rm = TRUE)
Michael
On Wed, Jan 11, 2012 at 11:18 PM, Spitzer, Matthew
<matthew.spit...@bmc.org> wrote:
> Hello,
> I would like to please ask for assistance with aggregate sum. I have a data
> set with consisting of two grouping variables (id, visit) and several other
> variables. I would like to sum the variables for each id and visit, but am
> having problems with na.rm. na.rm=TRUE seems to replace all NAs with zeros,
> or better stated results in a zero when summing a set of NAs. I would like
> to remove NAs when some NAs are present in a group (1+NA + NA =1 or NA + 1
> +1=2), but retain/keep the NA if the entire group consists of NAs (NA + NA +
> NA=NA).
>
> I have created an truncated example (my data set has many more rows):
>
> example <-
> structure(list(id = c(4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L,
> 4L, 4L, 4L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L, 12L,
> 12L, 12L, 12L, 43L, 43L, 43L, 43L, 43L, 43L, 43L, 43L, 43L, 43L,
> 43L, 43L), visit = c(3L, 3L, 3L, 3L, 5L, 5L, 5L, 9L, 9L, 9L,
> 9L, 12L, 12L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 5L, 9L, 9L, 12L, 12L,
> 12L, 3L, 3L, 3L, 3L, 5L, 5L, 5L, 5L, 12L, 12L, 12L, 12L), var1 = c(1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
> 1L, 1L, 1L, 1L, 1L), var2 = c(1L, NA, NA, NA, NA, 1L, NA, 0L,
> 1L, 0L, NA, 0L, NA, NA, NA, 1L, 0L, NA, 0L, 1L, 1L, 1L, NA, 1L,
> 0L, NA, NA, 1L, 1L, 0L, NA, 1L, NA, NA, 0L, 1L, 1L, 1L), var3 = c(NA,
> NA, NA, NA, 1L, 0L, 1L, NA, 1L, 1L, NA, 0L, 1L, NA, 0L, 1L, NA,
> 1L, 0L, NA, 1L, 0L, 1L, NA, NA, NA, NA, 1L, 1L, 1L, 1L, 0L, 1L,
> NA, NA, NA, NA, 1L), var4 = c(0L, 1L, NA, NA, NA, 1L, 1L, 0L,
> NA, NA, 0L, 1L, 1L, NA, 1L, 1L, 0L, 1L, 1L, NA, 1L, NA, 0L, 0L,
> 0L, NA, NA, NA, NA, NA, NA, 1L, 1L, NA, 0L, 0L, 0L, NA)), .Names = c("id",
> "visit", "var1", "var2", "var3", "var4"), class = "data.frame", row.names =
> c(NA,
> -38L))
> example<-as.data.frame(example)
>
> #generates 0s for groups with all NAs such as id 43, visit 3, var4 that I
> would like to be NA
> agex1 <-aggregate.data.frame(example,
> by=list(example$id,example$visit),FUN=sum,na.rm=TRUE)
>
> #discards sums with any NAs in it, including many data that I would like to
> analyze, too many NAs
> agex2<-aggregate.data.frame(example,
> by=list(example$id,example$visit),FUN=sum)
>
> na.action does not seem to work with data frames in this instance. I have
> tried to create a function to fix this, but have had great difficulty. I
> have thought about ddply but cannot figure out how to apply this. Would
> anyone be able to please suggest an alternate means of summing by group to
> retain NAs when I would like but not when they are part of an entire set of
> NAs? I would be very grateful for a suggestion for an alternate way to
> process these data.
>
> Thanks, Matt
>
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