1% Generated by roxygen2: do not edit by hand 2% Please edit documentation in R/model-lognorm.R 3\docType{class} 4\name{Zelig-lognorm-class} 5\alias{Zelig-lognorm-class} 6\alias{zlognorm} 7\title{Log-Normal Regression for Duration Dependent Variables} 8\arguments{ 9\item{formula}{a symbolic representation of the model to be 10estimated, in the form \code{y ~ x1 + x2}, where \code{y} is the 11dependent variable and \code{x1} and \code{x2} are the explanatory 12variables, and \code{y}, \code{x1}, and \code{x2} are contained in the 13same dataset. (You may include more than two explanatory variables, 14of course.) The \code{+} symbol means ``inclusion'' not 15``addition.'' You may also include interaction terms and main 16effects in the form \code{x1*x2} without computing them in prior 17steps; \code{I(x1*x2)} to include only the interaction term and 18exclude the main effects; and quadratic terms in the form 19\code{I(x1^2)}.} 20 21\item{model}{the name of a statistical model to estimate. 22For a list of other supported models and their documentation see: 23\url{http://docs.zeligproject.org/articles/}.} 24 25\item{data}{the name of a data frame containing the variables 26referenced in the formula or a list of multiply imputed data frames 27each having the same variable names and row numbers (created by 28\code{Amelia} or \code{\link{to_zelig_mi}}).} 29 30\item{...}{additional arguments passed to \code{zelig}, 31relevant for the model to be estimated.} 32 33\item{by}{a factor variable contained in \code{data}. If supplied, 34\code{zelig} will subset 35the data frame based on the levels in the \code{by} variable, and 36estimate a model for each subset. This can save a considerable amount of 37effort. You may also use \code{by} to run models using MatchIt 38subclasses.} 39 40\item{cite}{If is set to 'TRUE' (default), the model citation will be printed 41to the console.} 42 43\item{robust}{defaults to FALSE. If TRUE, zelig() computes robust standard errors based 44on sandwich estimators (see and ) based on the options in cluster.} 45 46\item{cluster}{if robust = TRUE, you may select a variable to define groups of correlated 47observations. Let x3 be a variable that consists of either discrete numeric values, character 48strings, or factors that define strata. Then 49 means that the observations can be correlated within the strata defined by the variable x3, 50 and that robust standard errors should be calculated according to those clusters. 51 If robust = TRUE but cluster is not specified, zelig() assumes that each observation falls 52 into its own cluster.} 53} 54\value{ 55Depending on the class of model selected, \code{zelig} will return 56 an object with elements including \code{coefficients}, \code{residuals}, 57 and \code{formula} which may be summarized using 58 \code{summary(z.out)} or individually extracted using, for example, 59 \code{coef(z.out)}. See 60 \url{http://docs.zeligproject.org/articles/getters.html} for a list of 61 functions to extract model components. You can also extract whole fitted 62 model objects using \code{\link{from_zelig_model}}. 63} 64\description{ 65Log-Normal Regression for Duration Dependent Variables 66} 67\details{ 68Additional parameters avaialable to many models include: 69\itemize{ 70 \item weights: vector of weight values or a name of a variable in the dataset 71 by which to weight the model. For more information see: 72 \url{http://docs.zeligproject.org/articles/weights.html}. 73 \item bootstrap: logical or numeric. If \code{FALSE} don't use bootstraps to 74 robustly estimate uncertainty around model parameters due to sampling error. 75 If an integer is supplied, the number of boostraps to run. 76 For more information see: 77 \url{http://docs.zeligproject.org/articles/bootstraps.html}. 78} 79} 80\section{Methods}{ 81 82\describe{ 83\item{\code{zelig(formula, data, model = NULL, ..., weights = NULL, by, bootstrap = FALSE)}}{The zelig function estimates a variety of statistical models} 84}} 85 86\examples{ 87library(Zelig) 88data(coalition) 89z.out <- zelig(Surv(duration, ciep12) ~ fract + numst2, model ="lognorm", data = coalition) 90summary(z.out) 91 92} 93\seealso{ 94Vignette: \url{http://docs.zeligproject.org/articles/zelig_lognorm.html} 95} 96