Zelig (version 3.5.5)

parse.formula: Parsing user-input formulas into multiple syntax

Description

Parse the input formula (or list of formulas) into the standard format described below. Since labels for this format will vary by model, parse.formula will evaluate a function describe.model, where model is given as an input to parse.formula.

If the describe.model function has more than one parameter for which ExpVar = TRUE and DepVar = TRUE, then the user-specified equations must have labels to match those parameters, else parse.formula should return an error. In addition, if the formula entries are not unambiguous, then parse.formula returns an error.

Usage

parse.formula(formula, model, data = NULL)

Arguments

formula

either a single formula or a list of formula objects

model

a character string specifying the name of the model

data

an optional data frame for models that require a factor response variable

Value

• The output is a list of formula objects with class c("multiple", "list"). Let's say that the name of the model is "bivariate.probit", and the corresponding describe function is describe.bivariate.probit, which identifies mu1 and mu2 as systematic components, and an ancillary parameter rho, which may be parameterized, but is estimated as a scalar by default.

Details

Acceptable user inputs are as follows:

lll{ User Input Output from parse.formula Same covariates, cbind(y1, y2) ~ x1 + x2 * x3 list(mu1 = y1 ~ x1 + x2 * x3, separate effects mu2 = y2 ~ x1 + x2 * x3, rho = ~ 1) With rho as a list(cbind(y1, y2) ~ x1 + x2, list(mu1 = y1 ~ x1 + x2, systematic equation rho = ~ x4 + x5) mu2 = y2 ~ x1 + x2, rho = ~ x4 + x5) With constraints list(mu1 = y1 ~ x1 + tag(x2, "x2"), list(mu1 = y1 ~ x1 + tag(x2, "x2"), (same variable) mu2 = y2 ~ x3 + tag(x2, "x2")) mu2 = y2 ~ x3 + tag(x2, "x2"), rho = ~ 1) With constraints list(mu1 = y1 ~ x1 + tag(x2, "z1"), list(mu1 = y1 ~ x1 + tag(x2, "z1"), (different variables) mu2 = y2 ~ x3 + tag(x4, "z1")) mu2 = y2 ~ x3 + tag(x4, "z1"), rho = ~ 1) }

See Also

parse.par, model.frame.multiple, model.matrix.multiple, and the full Zelig manual at http://gking.harvard.edu/zelig.

Examples

data(sanction)
formulae <- list(cbind(import, export) ~ coop + cost + target)
fml <- parse.formula(formulae, model = "bivariate.probit")
D <- model.frame(fml, data = sanction)