State Pattern Explorer
Explore how U.S. states relate to one another across CEV civic engagement indicators. Discover patterns, clusters, and relationships using interactive analysis tools.
About This Tool
What is the State Pattern Explorer?
The State Pattern Explorer is a suite of interactive visualization tools for analyzing civic engagement data across U.S. states. It helps researchers, policymakers, and civic organizations understand patterns in civic participation.
All tools work with the same underlying data from the Current Population Survey Civic Engagement Supplement (CEV), but present it in different ways to reveal different insights.
The Four Analysis Tools
A heatmap showing every state's performance on every indicator. Toggle between raw rates and z-scores. Good for getting the full picture and finding specific state-indicator combinations.
Shows how indicators relate to each other across states. Discover which civic activities tend to "travel together." Uses Spearman rank correlation.
Groups states by similar civic engagement profiles using hierarchical clustering. Identifies "types" of civic health patterns and which states share them.
Reduces many indicators to two dimensions for a bird's-eye view. Shows which states are similar overall and what drives the main differences.
Data Source: CEV Survey
The Civic Engagement Supplement (CEV) is part of the Current Population Survey, conducted by the U.S. Census Bureau. It is fielded in November of odd-numbered years.
- ~100,000 household interviews nationally
- Covers voting, volunteering, group membership, community involvement
- State-level estimates available for all 50 states + DC
- Self-reported participation in civic activities
Understanding Z-Scores
Many tools in this explorer use z-scores (standardized values) instead of raw rates. This allows fair comparison across indicators that have very different natural scales.
- z = 0: State is exactly at the national average
- z = +1: State is one standard deviation above average
- z = -1: State is one standard deviation below average
Key Limitations
- Self-reported data: Survey responses may be subject to social desirability bias
- Survey timing: Data is collected in November, which may affect responses about recent activities
- Sample sizes: Smaller states have larger margins of error
- Correlation ≠ causation: Patterns don't imply causal relationships
- Ecological fallacy: State-level patterns may not apply to individuals
- Point-in-time: These are snapshots; trends require comparing multiple years
How to Use These Tools
- Start with the Matrix for a comprehensive overview of all data
- Use Correlations to explore relationships between specific indicators
- Try Clusters to find states with similar profiles
- Use PCA to see the big picture and identify outliers
- Cross-reference findings across tools to build confidence in patterns
Tip: Each tool page has its own methodology panel with detailed explanations. Click the info button on the right side of any page to learn more.
Questions about methodology? Contact the NCoC research team.
State x Indicator Matrix
View a heatmap of all states across all indicators. Toggle between raw rates and standardized z-scores to compare performance across different measures.
Open matrix view →Indicator Correlations
Discover which indicators move together across states. See Spearman correlations in a heatmap and explore scatter plots for any indicator pair.
Explore correlations →State Clusters
Group states by their multi-indicator civic health profiles. Identify clusters of similar states and see what indicators define each group.
View clusters →PCA Visualization
Reduce the complexity of multiple indicators to two dimensions. See where states fall on the principal components and what indicators drive the variation.
Explore PCA →