amd_bi {quest} | R Documentation |
Amount of Missing Data - Bivariate (Pairwise Deletion)
Description
amd_bi
by default computes the proportion of missing data for pairs of
variables in a data.frame, with arguments to allow for counts instead of
proportions (i.e., prop
) or observed data rather than missing data
(i.e., ov
). It is bivariate in that each pair of variables is treated
in isolation.
Usage
amd_bi(data, vrb.nm, prop = TRUE, ov = FALSE)
Arguments
data |
data.frame of data. |
vrb.nm |
character vector of the colnames from |
prop |
logical vector of length 1 specifying whether the frequency of missing values should be returned as a proportion (TRUE) or a count (FALSE). |
ov |
logical vector of length 1 specifying whether the frequency of observed values (TRUE) should be returned rather than the frequency of missing values (FALSE). |
Value
data.frame of nrow = ncol = length(vrb.nm)
and rowames =
colnames = vrb.nm
providing the frequency of missing (or observed if
ov
= TRUE) values per pair of variables. If prop
= TRUE, the
values will range from 0 to 1. If prop
= FALSE, the values will
range from 0 to nrow(data)
.
See Also
Examples
amd_bi(data = airquality, vrb.nm = names(airquality)) # proportion of missing data
amd_bi(data = airquality, vrb.nm = names(airquality),
ov = TRUE) # proportion of observed data
amd_bi(data = airquality, vrb.nm = names(airquality),
prop = FALSE) # count of missing data
amd_bi(data = airquality, vrb.nm = names(airquality),
prop = FALSE, ov = TRUE) # count of observed data