Compute Number of Observations for Left Hand Side of Formula
After removing any artificial observations added by
addMarginal
, computes the number of
non-missing observations for all left-hand-side variables in
formula
. If formula
contains a term id(variable)
variable
is assumed to be a subject ID variable, and only unique
subject IDs are counted. If group is given and its value is the name of
a variable in the right-hand-side of the model, an additional object
nobsg
is returned that is a matrix with as many columns as there
are left-hand variables, and as many rows as there are levels to the
group
variable. This matrix has the further breakdown of unique
non-missing observations by group
. The concatenation of all ID
variables, is returned in a list
element id
.
nobsY(formula, group=NULL, data = NULL, subset = NULL, na.action = na.retain, matrixna=c('all', 'any'))
formula |
a formula object |
group |
character string containing optional name of a stratification variable for computing sample sizes |
data |
a data frame |
subset |
an optional subsetting criterion |
na.action |
an optional |
matrixna |
set to |
an integer, with an attribute "formula"
containing the
original formula but with an id
variable (if present) removed
d <- expand.grid(sex=c('female', 'male', NA), country=c('US', 'Romania'), reps=1:2) d$subject.id <- c(0, 0, 3:12) dm <- addMarginal(d, sex, country) dim(dm) nobsY(sex + country ~ 1, data=d) nobsY(sex + country ~ id(subject.id), data=d) nobsY(sex + country ~ id(subject.id) + reps, group='reps', data=d) nobsY(sex ~ 1, data=d) nobsY(sex ~ 1, data=dm) nobsY(sex ~ id(subject.id), data=dm)
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