ncases_ml {quest} | R Documentation |
Multilevel Number of Cases
Description
ncases_ml
computes the number cases and number of groups in the data
that are at least partially observed, given a specified frequency of observed
values across a set of columns. ncases_ml
allows the user to specify
the frequency of columns that need to be observed in order to count the case.
Groups can be excluded if no rows in the data for a group have enough
observed values to be counted as cases. This is simply a combination of
partial.cases
+ nrow_ml
. Note, ncases_ml
is essentially
a version of nrow_ml
that accounts for missing data.
Usage
ncases_ml(
data,
vrb.nm = str2str::pick(names(data), val = grp.nm, not = TRUE),
grp.nm,
ov.min = 1L,
prop = TRUE,
inclusive = TRUE
)
Arguments
data |
data.frame of data. |
vrb.nm |
a character vector of colnames from |
grp.nm |
character vector of colnames from |
ov.min |
minimum frequency of observed values required per row. If
|
prop |
logical vector of length 1 specifying whether |
inclusive |
logical vector of length 1 specifying whether the case
should be included if the frequency of observed values in a row is exactly
equal to |
Value
list with two elements providing the sample sizes (accouning for
missing data). The first element is named "within" and contains the number
of cases in the data. The second element is named "between" and contains
the number of groups in the data. Cases are counted if if the frequency of
observed values is greater than (or equal to, if inclusive
= TRUE).
See Also
nrow_ml
ncases_by
partial.cases
Examples
# NO MISSING DATA
# one grouping variable
ncases_ml(data = as.data.frame(ChickWeight), grp.nm = "Chick")
# multiple grouping variables
ncases_ml(data = mtcars, grp.nm = c("vs","am"))
# YES MISSING DATA
# only within
nrow_ml(data = airquality, grp.nm = "Month")
ncases_ml(data = airquality, grp.nm = "Month")
# both within and between
airquality2 <- airquality
airquality2[airquality2$"Month" == 6, "Ozone"] <- NA
nrow_ml(data = airquality2, grp.nm = "Month")
ncases_ml(data = airquality2, grp.nm = "Month")