neardate
Find the index of the closest value in data set 2, for each entry in data set one.
Description
A common task in medical work is to find the closest lab value to some index date, for each subject.
Usage
neardate(id1, id2, y1, y2, best = c("after", "prior"), nomatch = NA_integer_)
Arguments
id1 | vector of subject identifiers for the index group |
id2 | vector of identifiers for the reference group |
y1 | normally a vector of dates for the index group, but any orderable data type is allowed |
y2 | reference set of dates |
best | if |
nomatch | the value to return for items without a match |
Details
This routine is closely related to match
and to findInterval
, the first of which finds exact matches and the second closest matches. This finds the closest matching date within sets of exactly matching identifiers. Closest date matching is often needed in clinical studies. For example data set 1 might contain the subject identifier and the date of some procedure and data set set 2 has the dates and values for laboratory tests, and the query is to find the first test value after the intervention but no closer than 7 days.
The id1
and id2
arguments are similar to match
in that we are searching for instances of id1
that will be found in id2
, and the result is the same length as id1
. However, instead of returning the first match with id2
this routine returns the one that best matches with respect to y1
.
The y1
and y2
arguments need not be dates, the function works for any data type such that the expression c(y1, y2)
gives a sensible, sortable result. Be careful about matching Date and DateTime values and the impact of time zones, however, see as.POSIXct
. If y1
and y2
are not of the same class the user is on their own. Since there exist pairs of unmatched data types where the result could be sensible, the routine will in this case proceed under the assumption that "the user knows what they are doing". Caveat emptor.
Value
the index of the matching observations in the second data set, or the nomatch
value for no successful match
Author(s)
Terry Therneau
See Also
Examples
data1 <- data.frame(id = 1:10, entry.dt = as.Date(paste("2011", 1:10, "5", sep='-'))) temp1 <- c(1,4,5,1,3,6,9, 2,7,8,12,4,6,7,10,12,3) data2 <- data.frame(id = c(1,1,1,2,2,4,4,5,5,5,6,8,8,9,10,10,12), lab.dt = as.Date(paste("2011", temp1, "1", sep='-')), chol = round(runif(17, 130, 280))) #first cholesterol on or after enrollment indx1 <- neardate(data1$id, data2$id, data1$entry.dt, data2$lab.dt) data2[indx1, "chol"] # Closest one, either before or after. # indx2 <- neardate(data1$id, data2$id, data1$entry.dt, data2$lab.dt, best="prior") ifelse(is.na(indx1), indx2, # none after, take before ifelse(is.na(indx2), indx1, #none before ifelse(abs(data2$lab.dt[indx2]- data1$entry.dt) < abs(data2$lab.dt[indx1]- data1$entry.dt), indx2, indx1))) # closest date before or after, but no more than 21 days prior to index indx2 <- ifelse((data1$entry.dt - data2$lab.dt[indx2]) >21, NA, indx2) ifelse(is.na(indx1), indx2, # none after, take before ifelse(is.na(indx2), indx1, #none before ifelse(abs(data2$lab.dt[indx2]- data1$entry.dt) < abs(data2$lab.dt[indx1]- data1$entry.dt), indx2, indx1)))
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Licensed under the GNU General Public License.