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Construct Validity Estimate Calculator

Work out construct validity estimate instantly with clear inputs, formula shown and shareable results.

About Construct Validity Estimate Calculator

Average variance extracted is the mean squared loading, and convergent validity requires it above 0.50 - so 0.62 passes. The Fornell-Larcker criterion for discriminant validity requires the square root of AVE, 0.787 here, to exceed the correlation with any other construct, and 0.55 is comfortably below it.

Formulas

Average variance extracted

AVE = mean of squared standardised loadings

Fornell-Larcker criterion

sqrt(AVE) must exceed the inter-construct correlation

Worked example

With the default values below, Construct Validity Estimate Calculator returns Average Variance Extracted of 0.6200. Change any input above and every figure here is recalculated in your browser.

Inputs used

Average squared factor loadingaccepts 0–1
0.62
Number of itemsminimum 1
6
Correlation with the other constructaccepts -1–1
0.55

Results

Average Variance Extracted
0.6200
Square Root Of AVE
0.7874
Composite Reliability
0.9073
Discriminant Validity Check
Passes the Fornell-Larcker criterion

Step by step

  1. 1Values used
  2. 2Average variance extracted
  3. 3Fornell-Larcker criterion
  4. 4Average Variance Extracted= 0.6200
  5. 5Square Root Of AVE= 0.7874
  6. 6Composite Reliability= 0.9073
  7. 7Discriminant Validity Check= Passes the Fornell-Larcker criterion

Assumptions and limits

  • The result is derived only from the 3 inputs listed above. Anything not among them is not part of the calculation.
  • In particular, this calculator does not take inflation, tax or compounding frequency into account.
  • Figures are rounded for display to 4 decimal places, so totals built from several rounded parts can differ slightly from the unrounded arithmetic.

How these calculators are built and tested is described on the Methodology page. If a figure looks wrong, please report it.

Frequently Asked Questions

Why must AVE exceed 0.50?

Because below that the construct explains less of its indicators' variance than measurement error does, so the latent variable is poorly defined.

Is Fornell-Larcker still the standard?

It remains widely reported, though the HTMT ratio is now often preferred because it detects discriminant validity problems more sensitively.

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