Zelig: Everyone's Statistical Software

Zelig is an easy-to-use program that can estimate, and help interpret the results of, an enormous range of statistical models. It literally is “everyone's statistical software” because Zelig's simple unified framework incorporates everyone else's (R) code. We also hope it will become “everyone's statistical software” for applications and teaching, and so have designed Zelig so that anyone can easily use it or add their programs to it. Zelig also comes with infrastructure that facilitates the use of any existing method, such as by allowing multiply imputed data for any model, and mimicking the program Clarify (for Stata) that takes the raw output of existing statistical procedures and translates them into quantities of direct interest.

Version: 3.4-8
Depends: R (≥ 2.6.0), MASS, boot
Suggests: VGAM (≥ 0.7-5), MCMCpack (≥ 0.8-2), mvtnorm, survival, sandwich (≥ 2.1-0), zoo (≥ 1.5-0), coda, nnet, sna, gee, systemfit, mgcv, lme4, anchors (≥ 2.0), survey, quantreg
Published: 2010-01-21
Author: Kosuke Imai, Gary King, Olivia Lau
Maintainer: Kosuke Imai <kimai at Princeton.Edu>
License: GPL (≥ 2)
URL: http://gking.harvard.edu/zelig
In views: Econometrics, Finance, SocialSciences
CRAN checks: Zelig results

Downloads:

Package source: Zelig_3.4-8.tar.gz
MacOS X binary: Zelig_3.4-8.tgz
Windows binary: Zelig_3.4-8.zip
Reference manual: Zelig.pdf
Vignettes: Fit an Analysis of Variance Model
ARIMA Models for Time Series Data
Bivariate Logistic Regression for Two Dichotomous Dependent Variables
Bivariate Probit Regression for Dichotomous Dependent Variables
Compound Hierarchical Ordered Probit for Survey Vignettes
Social Network Complementary Log Log Regression for Dichotomous Dependent Variables
Cox Proportional Hazards Regression for Duration Dependent Variables
Hierarchical Multinomial-Dirichlet Ecological Inference Model
Quinn's Dynamic Ecological Inference
Hierarchical Ecological Inference Model for 2x2 tables
Exponential Regression for Duration Dependent Variables
Bayesian Factor Analysis
Mixed Data Factor Analysis
Ordinal Data Factor Analysis
Gamma Regression for Continuous, Positive Dependent Variables
Generalized Estimating Equation for Gamma Regression
Gamma mixed effects linear regression
Network Gamma Regression for Continuous, Positive Proximity Matrix Dependent Variables
Survey-Weighted Gamma Regression for Continuous, Positive Dependent Variables
One Dimensional Item Response Mode
K-Dimensional Item Response Model
Logistic Regression for Dichotomous Dependent Variables
Bayesian Logistic Regression for Dichotomous Dependent Variables
Generalized Additive Model for Dichotomous Dependent Variables
Generalized Estimating Equation for Logistic Regression
Mixed effects logistic regression
Network Logistic Regression for Dichotomous Proximity Matrix Dependent Variables
Survey-Weighted Logistic Regression for Dichotomous Dependent Variables
Log-Normal Regression for Duration Dependent Variables
Least Squares Regression for Continuous Dependent Variables
Mixed effects linear regression
Network Least Squares Regression for Continuous Proximity Matrix Dependent Variables
Multinomial Logistic Regression for Dependent Variables with Unordered Categorical Values
Bayesian Multinomial Logistic Regression for Dependent Variables with Unordered Categorical Values
Negative Binomial Regression for Event Count Dependent Variables
Normal Regression for Continuous Dependent Variables
Bayesian Normal Linear Regression
Generalized Additive Model for Continuous Dependent Variables
Generalized Estimating Equation for Normal Regression
Network Normal Regression for Continuous Proximity Matrix Dependent Variables
Survey-Weighted Normal Regression for Continuous Dependent Variables
Ordinal Logistic Regression for Ordered Categorical Dependent Variables
Ordinal Probit Regression for Ordered Categorical Dependent Variables
Bayesian Ordered Probit Regression
Poisson Regression for Event Count Dependent Variables
Bayesian Poisson Regression
Generalized Additive Model for Count Dependent Variables
Generalized Estimating Equation for Poisson Regression
Mixed effects poisson regression
Ordinal Logistic Regression for Ordered Categorical Dependent Variables
Survey-Weighted Poisson Regression for Event Count Dependent Variables
Probit Regression for Dichotomous Dependent Variables
Bayesian Probit Regression for Dichotomous Dependent Variable
Generalized Additive Model for Dichotomous Dependent Variables
Generalized Estimating Equation for Probit Regression
Mixed effects probit regression
Network Probit Regression for Dichotomous Proximity Matrix Dependent Variables
Survey-Weighted Probit Regression for Dichotomous Dependent Variables
Quantile Regression for Continuous Dependent Variables
Rare Events Logistic Regression for Dichotomous Dependent Variables
Quantile Regression for Continuous Dependent Variables
Seemingly Unrelated Regression
Three Stage Least Squares
Linear regression for Left-Censored Dependet Variable
Bayesian Linear Regression for a Censored Dependent Variable
Two Stage Least Squares
Weibull Regression for Duration Dependent Variables
Old sources: Zelig archive

Reverse dependencies:

Reverse depends: VDCutil, boolean
Reverse imports: boolean
Reverse suggests: Amelia, accuracy, mice