Table 1 –

Latent Class Solutions and Fit Indices for the Time 1 and Time 2 Assessments Using Symptom Occurrence Ratings^a

Time 1 Assessment – Prior to Next Dose of Chemotherapy
Model	LL	AIC	BIC	VLMR	Entropy
2 Class	−13465.34	27032.68	27277.55	2375.10****	.84
3 Classb	−13217.76	26589.51	26959.21	495.17****	.83
4 Class	−13084.89	26375.78	26870.31	265.73ns	.80
Time 2 Assessment – Following the Next Dose of Chemotherapy
2 Class	−13286.83	26675.67	26920.53	2320.59****	.83
3 Classb	−13021.47	26196.94	26566.64	530.73****	.81
4 Class	−12892.35	25990.71	26485.24	258.23ns	.79

^nsNot significant

^*p < .05

^**p < .01

^***p < .001

^****p < .0001

^aIn 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.

^bThe 3-class solution was selected because the VLMR was significant for the 3-class solution, indicating that three classes fit the data better than two classes, and the VLMR was not significant for the 4-class solution, indicating that too many classes had been extracted.

Note. LL = log-likelihood; AIC = Akaike Information Criterion, BIC = Bayesian Information Criterion; VLMR = Vuong-Lo-Mendell-Rubin likelihood ratio test for the K vs. K-1 model.