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