Polychoric Matrix
VerifiedPsychometrics (legacy hub)
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Estimates correlations between ORDINAL items (Likert scales, binary items) under the assumption of an underlying continuous bivariate normal distribution.
Pearson correlations on ordinal items are ATTENUATED — the discrete nature of the response truncates true correlations toward zero. Polychoric (for ordinal × ordinal) and tetrachoric (for binary × binary) correlations recover the underlying continuous correlation. Reports the polychoric matrix, convergence diagnostics, and matrix positivity (positive-definite required for downstream EFA / CFA).
Worked example
How do we correlate ordinal (Likert) items properly?
Polychoric correlations estimate the latent continuous correlation behind ordinal items — more appropriate than Pearson for Likert data before factoring.
Polychoric correlations among items ranged .35–.68, higher than the Pearson values, yielding a cleaner factor solution.
Polychoric correlations were used for the ordinal items (range .35–.68) prior to factor analysis.
When to use it
- EFA / CFA input prep for ordinal Likert items30-item depression scale with 4-point Likert responses.
- Tetrachoric matrix for binary-item analysis60-item multiple-choice math test (0/1 scoring) on n=400.
When NOT to — use instead
- Continuous (interval/ratio) itemsPearson is appropriate for continuous data — polychoric is unnecessary and adds estimator noise. → KMO + Bartlett
- Likert with 7+ response options5+ point Likert can be treated as approximately continuous; Pearson is acceptable. → KMO + Bartlett
- Single item or pair (not a matrix)Polychoric MATRIX needs ≥ 3 items. → AVE + CR + HTMT
- Sample too small (n < 200)Polychoric estimates are noisy on small n. → KMO + Bartlett
Assumptions (and what to do if they fail)
Check: See the assumption diagnostics in the workspace.
If violated: The workspace flags this and suggests a robust or nonparametric alternative.
Check: See the assumption diagnostics in the workspace.
If violated: The workspace flags this and suggests a robust or nonparametric alternative.
Check: See the assumption diagnostics in the workspace.
If violated: The workspace flags this and suggests a robust or nonparametric alternative.
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