Paste your CFA loadings and get McDonald's omega (composite reliability) and AVE with interpretation. The modern alternative to Cronbach's alpha. Free.
McDonald's omega (ω), equivalent to composite reliability (CR), estimates internal consistency from the standardized factor loadings of a one-factor model. Unlike Cronbach's alpha it does not assume tau-equivalence (equal loadings), which is why it is the metric reviewers ask for when your CFA loadings differ. AVE (average variance extracted) goes alongside omega as convergent-validity evidence.
| Value | Interpretation |
|---|---|
| ω ≥ .90 | Excellent |
| ω ≥ .80 | Good |
| ω ≥ .70 | Acceptable |
| ω < .70 | Insufficient |
| ω > .95 | May indicate item redundancy (near-duplicate items) |
| AVE ≥ .50 | Adequate convergent validity |
| AVE < .50 | Low |
ω = (Σλ)² / [(Σλ)² + Σ(1 − λ²)]
AVE = Σλ² / k, where k is the number of items.
Standardized loadings (λ) come from your one-factor CFA (lavaan, Mplus, JASP) and must lie between −1 and 1. Loadings outside that range are flagged: they are unstandardized.
McDonald, R. P. (1999). Test Theory: A Unified Treatment. Erlbaum. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.