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measurement-psychometrics

Evaluates reliability and validity of social science measurement scales using factor models and psychometrics.

Updated Aug 27, 2026
Search Tags:#psychometrics#sem#irt#scale validation#cronbach alpha#efa cfa#measurement invariance
One-click install
npx skills add https://github.com/Yuuqq/claude-social-science-skills --skill measurement-psychometrics
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: measurement-psychometrics
Source: https://github.com/Yuuqq/claude-social-science-skills/tree/main/social-science-skills/measurement-psychometrics
Command: npx skills add https://github.com/Yuuqq/claude-social-science-skills --skill measurement-psychometrics

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pingouin, factor-analyzer, semopy, reliability, girth, networkx, community, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill solves the problem of building and validating social science measurement instruments so that your scales are reliable, valid, and comparable across groups.

Core Features & Use Cases

  • Reliability & internal consistency: Compute Cronbach’s alpha and interpret it alongside omega-based reliability (including omega hierarchical) and item-total diagnostics.
  • Factor structure validation: Run EFA and CFA to estimate dimensionality and test hypothesized measurement models.
  • Advanced measurement validation: Perform measurement invariance testing across groups, fit bifactor models, and (when appropriate) apply IRT and network psychometrics for deeper scale evaluation.
  • Scale scoring: Construct composite indices (simple, weighted, or standardized) based on your indicators and chosen measurement model.

Quick Start

Use this skill to validate a Likert-scale by running EFA then CFA, reporting reliability (alpha/omega), and testing measurement invariance across two groups.

Frequently Asked Questions about measurement-psychometrics

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I validate a Likert scale using EFA and CFA in Python?▼

To validate a Likert scale, run exploratory factor analysis to estimate dimensionality, then confirm the hypothesized structure using confirmatory factor analysis to ensure factor structure validity.

What is measurement invariance testing and when do I need it?▼

Measurement invariance testing evaluates whether scale constructs are comparable across different groups, ensuring that observed group differences reflect true trait differences rather than measurement bias.

Can I run item response theory and bifactor models using Python psychometrics libraries?▼

Yes, you can apply item response theory and fit bifactor models for deeper scale evaluation using specialized Python libraries designed for advanced psychometric workflows.

Does this workflow support building composite indices from standardized items?▼

Yes, you can construct composite indices using simple, weighted, or standardized scoring methods based on your chosen measurement model and indicator variables.

What are the limitations of using network psychometrics for scale validation?▼

Network psychometrics provides deeper scale evaluation but should be applied cautiously, as it assumes complex inter-item relationships that may not suit simple unidimensional Likert scales.

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