Latent Class Analysis Calculator
Identify hidden groups in categorical data using the EM algorithm.
Model Summary
Observations:8
Variables:3
Classes:2
Iterations:16
Model Fit Statistics
Log-Likelihood:-14.4589
AIC:42.9179
BIC:43.4740
Entropy R²:0.8418
Class Proportions
Class 133.5% (n=3)
Class 266.5% (n=5)
Item Response Probabilities
| Item | Class 1 | Class 2 |
|---|---|---|
| Item 1 | 0.1% | 75.1% |
| Item 2 | 0.1% | 75.1% |
| Item 3 | 27.7% | 80.0% |
Posterior Probabilities (first 10)
| Obs | P(Class 1) | P(Class 2) | Assignment |
|---|---|---|---|
| 1 | 0.000 | 1.000 | 2 |
| 2 | 0.000 | 1.000 | 2 |
| 3 | 0.001 | 0.999 | 2 |
| 4 | 0.001 | 0.999 | 2 |
| 5 | 0.967 | 0.033 | 1 |
| 6 | 0.740 | 0.260 | 1 |
| 7 | 0.000 | 1.000 | 2 |
| 8 | 0.967 | 0.033 | 1 |
Interpretation
Entropy R² of 0.842 indicates excellent classification quality. Item probabilities > 50% (highlighted) characterize each class.