R/model-probit-gee.R

#' Generalized Estimating Equation for Probit Regression
#' @param formula a symbolic representation of the model to be
#'   estimated, in the form \code{y ~ x1 + x2}, where \code{y} is the
#'   dependent variable and \code{x1} and \code{x2} are the explanatory
#'   variables, and \code{y}, \code{x1}, and \code{x2} are contained in the
#'   same dataset. (You may include more than two explanatory variables,
#'   of course.) The \code{+} symbol means ``inclusion'' not
#'   ``addition.'' You may also include interaction terms and main
#'   effects in the form \code{x1*x2} without computing them in prior
#'   steps; \code{I(x1*x2)} to include only the interaction term and
#'   exclude the main effects; and quadratic terms in the form
#'   \code{I(x1^2)}.
#' @param model the name of a statistical model to estimate.
#'   For a list of other supported models and their documentation see:
#'   \url{http://docs.zeligproject.org/articles/}.
#' @param data the name of a data frame containing the variables
#'   referenced in the formula or a list of multiply imputed data frames
#'   each having the same variable names and row numbers (created by
#'   \code{Amelia} or \code{\link{to_zelig_mi}}).
#' @param ... additional arguments passed to \code{zelig},
#'   relevant for the model to be estimated.
#' @param by a factor variable contained in \code{data}. If supplied,
#'   \code{zelig} will subset
#'   the data frame based on the levels in the \code{by} variable, and
#'   estimate a model for each subset. This can save a considerable amount of
#'   effort. You may also use \code{by} to run models using MatchIt
#'   subclasses.
#' @param cite If is set to 'TRUE' (default), the model citation will be printed
#'   to the console.
#' @param corstr:character string specifying the correlation structure: "independence",
#' "exchangeable", "ar1", "unstructured" and "userdefined"
#' @param See geeglm in package geepack for other function arguments.
#' @param id: where id is a variable which identifies the clusters. The data should be
#' sorted by id and should be ordered within each cluster when appropriate
#' @param corstr: character string specifying the correlation structure: "independence",
#' "exchangeable", "ar1", "unstructured" and "userdefined"
#' @param geeglm: See geeglm in package geepack for other function arguments
#'
#' @details
#' Additional parameters avaialable to this model include:
#' \itemize{
#'   \item \code{weights}: vector of weight values or a name of a variable in the dataset
#'   by which to weight the model. For more information see:
#'   \url{http://docs.zeligproject.org/articles/weights.html}.
#'   \item \code{bootstrap}: logical or numeric. If \code{FALSE} don't use bootstraps to
#'   robustly estimate uncertainty around model parameters due to sampling error.
#'   If an integer is supplied, the number of boostraps to run.
#'   For more information see:
#'   \url{http://docs.zeligproject.org/articles/bootstraps.html}.
#' }
#' @return Depending on the class of model selected, \code{zelig} will return
#'   an object with elements including \code{coefficients}, \code{residuals},
#'   and \code{formula} which may be summarized using
#'   \code{summary(z.out)} or individually extracted using, for example,
#'   \code{coef(z.out)}. See
#'   \url{http://docs.zeligproject.org/articles/getters.html} for a list of
#'   functions to extract model components. You can also extract whole fitted
#'   model objects using \code{\link{from_zelig_model}}.
#'
#'@examples
#' data(turnout)
#' turnout$cluster <- rep(c(1:200), 10)
#' sorted.turnout <- turnout[order(turnout$cluster),]
#' z.out1 <- zelig(vote ~ race + educate, model = "probit.gee",
#' id = "cluster", data = sorted.turnout)
#' summary(z.out1)
#'
#' @seealso Vignette: \url{http://docs.zeligproject.org/articles/zelig_probitgee.html}
#' @import methods
#' @export Zelig-probit-gee
#' @exportClass Zelig-probit-gee
#'
#' @include model-zelig.R
#' @include model-binchoice-gee.R

zprobitgee <- setRefClass("Zelig-probit-gee",
                          contains = c("Zelig-binchoice-gee"))

zprobitgee$methods(
  initialize = function() {
    callSuper()
    .self$name <- "probit-gee"
    .self$link <- "probit"
    .self$description <- "General Estimating Equation for Probit Regression"
    .self$wrapper <- "probit.gee"
  }
)

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Zelig documentation built on Jan. 8, 2021, 2:26 a.m.