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zelig2

A modern R package for statistical model estimation, counterfactual simulation, and visualization --- building on the Zelig framework developed at Harvard's Institute for Quantitative Social Science (IQSS).

Background

The original Zelig package (Imai, King, and Lau 2007, 2008) introduced a powerful idea: unify statistical model estimation behind a single interface --- zelig() -> setx() -> sim() -> plot() --- so that researchers could move seamlessly from model fitting to substantively meaningful quantities of interest (expected values, predicted values, and first differences). Zelig operationalized the simulation-based approach to statistical interpretation described in King, Tomz, and Wittenberg (2000, AJPS).

zelig2 is a ground-up reimplementation of Zelig that preserves its core workflow while modernizing the internals. The estimation--simulation--visualization pipeline remains the same; zelig2 updates the package architecture, plotting system, and feature set for contemporary applied research.

The zelig2 Workflow

Every analysis in zelig2 follows four steps:

library(zelig2)

z <- zelig2(y ~ x1 + x2, model = "ls", data = mydata)   # 1. Estimate
z <- setx(z, x1 = 10)                                     # 2. Set scenario
z <- sim(z)                                                # 3. Simulate
plot(z)                                                    # 4. Visualize
  1. Estimate a model with zelig2().
  2. Set counterfactual covariate values with setx() (and optionally setx1() for contrasts).
  3. Simulate quantities of interest --- expected values, predicted values, and first differences --- with sim().
  4. Visualize the results with plot().

Why zelig2?

Zelig (Imai, King, and Lau) was last updated in 2020 and relies on setRefClass, base R graphics, and 16 dependencies. zelig2 retains Zelig's workflow while addressing these limitations:

Feature Zelig (Imai, King, and Lau) zelig2
Survey weights Separate model types (normal.survey); buggy Seamless weights =; matches svyglm() exactly
Fixed effects Not supported Built-in via fixest
Robust SEs Not supported HC0--HC4, cluster, bootstrap
Plotting Base R ggplot2 + patchwork
Dependencies 16 7
OOP style setRefClass (mutable) S3 (functional, immutable)
Last updated 2020 Active

Supported Models

Model model = Category
Least Squares (OLS) "ls" Continuous
Logistic Regression "logit" Binary
Probit Regression "probit" Binary
Poisson Regression "poisson" Count
Negative Binomial "negbin" Count
Gamma Regression "gamma" Continuous
Tobit (Censored) "tobit" Continuous
Quantile Regression "quantile" Continuous

All models except tobit and quantile support fixed effects via fixest.

Quick Example

Using data from the U.S. Census Bureau's Household Pulse Survey, we estimate the relationship between household income and food insecurity:

library(zelig2)

z <- zelig2(food_insecure ~ age + college + income_k,
            model = "logit", data = pulse, num = 1000L)

z <- setx(z, age = 35, college = 0, income_k = 50)
z <- setx1(z, age = 35, college = 0, income_k = 100)
z <- sim(z)

summary(z)

--- Simulation Summary ( 1000  draws) ---
Expected Values:
  Mean: 0.2028  SD: 0.0038  [0.1955, 0.2104]
First Differences:
  Mean: -0.1204  SD: 0.0026  [-0.1254, -0.1154]

Moving from $50k to $100k in household income reduces the predicted probability of food insecurity by approximately 12 percentage points (95% CI: [-0.125, -0.115]).

Installation

# Install from GitHub
devtools::install_github("tlcaputi/zelig2", subdir = "r")

Acknowledgments

zelig2 builds directly on the intellectual foundation of the Zelig project at Harvard's Institute for Quantitative Social Science (IQSS). The core idea --- estimate a model, set counterfactual scenarios, simulate quantities of interest, and visualize --- originates with:

  • King, G., Tomz, M., and Wittenberg, J. (2000). "Making the Most of Statistical Analyses: Improving Interpretation and Presentation." American Journal of Political Science, 44(2), 347--361.
  • Imai, K., King, G., and Lau, O. (2007). "Zelig: Everyone's Statistical Software." https://github.com/IQSS/Zelig
  • Imai, K., King, G., and Lau, O. (2008). "Toward a Common Framework for Statistical Analysis and Development." Journal of Computational and Graphical Statistics, 17(4), 892--913.

The Zelig package was subsequently maintained by Choirat, Honaker, Imai, King, and Lau. zelig2 would not exist without their foundational work.