model.frame.multiple {Zelig} | R Documentation |
Use model.frame.multiple
after parse.par
to create a
data frame of the unique variables identified in the formula (or list
of formulas).
model.frame.multiple(formula, data, eqn = NULL, ...)
formula |
a list of formulas of class "multiple" , returned from parse.par |
data |
a data frame containing all the variables used in formula |
eqn |
an optional character string or vector of character strings specifying
the equations (specified in describe.mymodel ) for which you would like to
pull out the relevant variables. |
... |
additional arguments passed to
model.frame.default |
The output is a data frame (with a terms attribute) containing all the
unique explanatory and response variables identified in the list of
formulas. By default, missing (NA
) values are listwise deleted.
If as.factor
appears on the left-hand side, the response
variables will be returned as an indicator (0/1) matrix with columns
corresponding to the unique levels in the factor variable.
If any formula contains more than one tag
statement, model.frame.multiple
will return the original variable in the data frame and use the tag
information in the terms
attribute only.
Kosuke Imai <kimai@princeton.edu>; Gary King <king@harvard.edu>; Olivia Lau <olau@fas.harvard.edu>; Ferdinand Alimadhi <falimadhi@iq.harvard.edu>
model.matrix.default
, parse.formula
and the full Zelig manual at
http://gking.harvard.edu/zelig
## Not run: data(sanction) formulae <- list(import ~ coop + cost + target, export ~ coop + cost + target) fml <- parse.formula(formulae, model = "bivariate.logit") D <- model.frame(fml, data = sanction) ## End(Not run)