TABLE 3.
Goodness of fit of latent class models including six KSHV serological assays (IMT IFA-LANA, IMT IFA-lytic, IMT whole-virus ELISA, MAP ELISA, ABI ELISA, and DIAVIR)
| Statistic | Value (n = 375)
|
||
|---|---|---|---|
| LC model 1 | LC model 2 | LC model 3 | |
| Degree of freedom | 57 | 50 | 43 |
| L-square value (L2)a | 985.07 | 86.22 | 38.3 |
| Chi-square value | 4,039.60 | 100.62 | 38.04 |
| P value | <0.0001 | 0.0011 | 0.5 |
| BICb | 647.24 | −210 | −216 |
| AICb | 871.07 | −13.77 | −47.68 |
| CAICb | 590.24 | −260.12 | −259.54 |
| No. (%) of samples in LC model | 166 (44) | 115 (31) | 94 (25) |
a
The L-square value (L2) indicates the best fit of the LC model. The larger the value, the poorer the model fits the data.
b
BIC, AIC, and CAIC are statistical parameters which take into account the parsimony (degrees of freedom) of the model. BIC (Bayesian information criterion), AIC (Akaike information criterion), and CAIC (consistent AIC) measure the goodness of fit of each model (the lower their values, the better the model).