Add Marginal Observations
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)
data |
a data frame |
... |
a list of names of variables to marginalize |
label |
category name for added marginal observations |
margloc |
location for marginal category within factor variable
specifying categories. Set to |
nested |
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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