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Given a data frame and the names of variable, doubles the
data frame for each variable with a new category
"All" by default, or by the value of label.
A new variable .marginal. is added to the resulting data frame,
with value "" if the observation is an original one, and with
value equal to the names of the variable being marginalized (separated
by commas) otherwise. If there is another stratification variable
besides the one in ..., and that variable is nested inside the
variable in ..., specify nested=variable name to have the value
of that variable set fo label whenever marginal observations are
created for .... See the state-city example below.
addMarginal(data, ..., label = "All", margloc=c('last', 'first'), nested)
a data frame
a list of names of variables to marginalize
category name for added marginal observations
location for marginal category within factor variable
specifying categories. Set to "first" to override the
default - to put a category with value label as the first
category.
a single unquoted variable name if used
d <- expand.grid(sex=c('female', 'male'), country=c('US', 'Romania'),
reps=1:2)
addMarginal(d, sex, country)
# Example of nested variables
d <- data.frame(state=c('AL', 'AL', 'GA', 'GA', 'GA'),
city=c('Mobile', 'Montgomery', 'Valdosto',
'Augusta', 'Atlanta'),
x=1:5, stringsAsFactors=TRUE)
addMarginal(d, state, nested=city) # cite set to 'All' when state is
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