Table 1

Return to:   Trajectories of Pain in Adolescents: A Prospective Cohort Study ospective Cohort Study

Goodness of fit statistics for models of pain trajectory from latent class growth analysis.

ModelAICLLBICLLCAICLLTest of improvement in model fit compared to model with 1 less clustera
Back pain
3 Cluster703370907101<0.001
4 Cluster694770257040<0.001
5 Cluster691770167035<0.001
6 Cluster690570257048<0.001
7 Cluster6900704070670.01
8 Cluster6900706170920.19


Facial pain
2 Cluster431443514358<0.001
3 Cluster427743344345<0.001
4 Cluster425143294344<0.001
5 Cluster4246434543640.008
6 Cluster4252437243950.58


Headache
2 Cluster761676527659<0.001
3 Cluster734073977408<0.001
4 Cluster728873667381<0.001
5 Cluster727373727391<0.001
6 Cluster725673767399<0.001


Stomach pain
2 Cluster700370397046<0.001
3 Cluster688569436954<0.001
4 Cluster683469126927<0.001
5 Cluster682269216940<0.001
6 Cluster6822694269650.17
AIC, Akaike’s information criterion; BIC, Bayes’ information criteria; CAIC, consistent Akaike’s information criterion; LL, log-likelihood. Optimal models based on goodness of fit statistics shown in bold.