JFK Case Study › Survey Explorer Model Builder Inside the Model All-or-Nothing Fine-Tuning Non-Response Test
November 1963 · Harris/Newsweek Survey

Model Builder

Inspect & challenge the published model

Refit the model with whichever predictors you choose. Pick one of three outcomes — Presidential Approval, Vote Intention (Kennedy vs. Goldwater), or Tax Cut Support — then add or remove survey questions, restrict the fit to a subgroup, or build a competing model from scratch.

The simulators and stress test are scoped to the Approval outcome. To explore drivers of Vote Intention or Tax Cut Support, use this Model Builder. The Survey Explorer works across all three outcomes.

How to Use This Tool

Pick the outcome you want to model, then check the predictor variables you want to test, then click Run Analysis to fit. If you've chosen Approval, the published model's six variables are pre-selected as a starting point.

1. Pick an outcome

Three outcomes are available: Presidential Approval (the case study's headline), Vote Intention (Kennedy vs. Goldwater), and Tax Cut Support. Switch outcomes anytime with the chooser at the top of the variable section.

2. Pick predictors

Use the search box and category buttons to find variables across Political, Policy, Evaluation, and Demographics. For Approval, six published-model predictors are pre-checked; for Vote Intention and Tax Cut Support, start from scratch or use Auto-Build below. Run Analysis is capped at 20 predictors; Auto-Build searches the full set and isn't capped.

3. Fit and read

Click Run Analysis to fit the model with whatever variables you've checked. Or use Auto-Build Standard to let the algorithm search all variables automatically, or Auto-Build Actionable Predictors to weight selection toward issue evaluations and policy attitudes over fixed demographic context.

Optional: subgroup

By default, the model is fit on all 1,283 respondents. Optionally restrict it to one subgroup at a time using the Whose data? panel — e.g. just Republicans, or just respondents under 35 — to see how the model behaves within that group. Subgroup levels with fewer than 100 respondents are hidden.

Want to see the math? The companion page Inside the Model walks through how one respondent's six answers become a predicted probability, and how those probabilities aggregate into the approval headline. Recommended for first-time visitors and academic readers.
After you run — what to expect

Review results

Results show how well the model predicts the outcome and how much each predictor contributes. The Other Variables in This Survey section lists every variable not yet in your model — each card shows whether adding it would likely improve fit.

Use the simulator

Click Launch in the Simulator panel to open an interactive tool. Set any combination of survey responses — e.g. economy rating "Poor" and Vietnam handling "Excellent" — and watch the predicted approval probability update instantly.

Iterate and compare

Each run is saved in the Saved Analyses tray. Click Load to restore a run, or Pin two runs to view them side by side. Each card shows Tjur R², AUC, and Brier — higher Tjur R² and AUC, lower Brier means a better-performing model.

If you ran with a synthetic variable, results show three sections:

Full Model

Complete model including all selected predictors and the synthetic variable.

Base Model

Model performance without the synthetic variable.

Synthetic Variable Performance

How well the synthetic met its specifications and its impact on model fit.

What are you trying to predict?

Choose the outcome your model will try to explain.

Required
Loading outcomes…

Survey Questions to Include in Your Model

Download Harris/Newsweek Questionnaire (PDF)
For Approval, six predictors are pre-checked — the published model. For Vote Intention and Tax Cut Support, no variables are pre-checked. Check the variables you want to test, or scroll down to Run Analysis or Auto-Build.
Loading variables…
Outcome: …
0 of … predictor variables selected
Advanced options — synthetic-variable vulnerability check (optional)

Vulnerability check. Inserts a synthetic predictor with a known relationship to the outcome. If the synthetic shows up as a significant predictor in the result, the model may be absorbing signal that doesn't really belong to your chosen variables — a sign it's vulnerable to omitted variables of similar strength.

r =
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The model you're about to fit
Predictors (X)
No predictors selected yet. Check variable cards above or click Auto-Build below.
Outcome (Y)
…

A logistic regression model uses the predictors on the left to estimate the probability of the outcome on the right. This summary updates as you change your selection — and shows exactly what gets submitted when you click Run Analysis. Auto-Build ignores this selection and chooses predictors for you.

Run Analysis

Build a model from exactly the predictors you've selected above. Full analyst control.

Returns: model fit, predictor strengths, calibration, and an interactive simulator.

Auto-Build

Ignores your selection above. Searches the full set of available predictors and picks the best subset for you. Actionable Predictors is selected by default — switch to Standard below if you prefer pure fit:

Finds the predictors that can actually be changed — useful for planning.

Returns: a chosen subset of predictors plus full model fit, strengths, and an interactive simulator.

Auto-Building Optimal Model… 0s

Section 1: Full Model Performance

Complete model including all predictor variables and the synthetic variable