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. Author manuscript; available in PMC: 2020 May 18.
Published in final edited form as: Eur J Cancer Care (Engl). 2016 Jan 18;26(3):10.1111/ecc.12437. doi: 10.1111/ecc.12437

Table 2 -.

Latent Transition Solutions and Fit Indices for Two-to-Two and Three-to-Three Classes Using Symptom Occurrence Ratingsa for Time 1 to Time 2

Model LL AIC BIC Entropy
2 classes −26645.54 53397.07 53651.95 .86
3 classesb −26073.41 52312.82 52711.97 .85
a

In order to have a sufficient number of patients with each symptom to perform the latent class analyses, the MSAS symptoms that occurred in at least 40% of the patients were identified. This criterion was selected to provide assurance that sufficient information was available to identify classes that were not sample-specific, due to infrequent reports of symptoms. A total of 25 out of 32 symptoms from the MSAS occurred in >40% of the patients.

b

The 3-to-3-class solution was selected because the BIC was smaller than the 2-to-2-class solution.

Note. LL = log-likelihood; AIC = Akaike Information Criterion, BIC = Bayesian Information Criterion.