General and subspecialist pediatrician perspectives on barriers and strategies for referral: a latent profile analysis

Table 1 Latent profile models for perceived barriers to pediatric subspecialty care

	AIC	SSA BIC	LMR-LRT	p-value	BLRT	p-value	Entropy	Classification probabilities
2-profile	2838.052	2847.377	-1597.26	< .0001	-1597.26	< .0001	0.833	.945-.964
3-profile	2772.165	2786.356	-1396.03	0.3523	-1396.03	< .0001	0.835	.865-.930
4-profile	2756.176	2775.232	-1351.08	0.2633	-1351.08	< .0001	0.848	.873-.915
5-profile	2750.719	2774.64	-1331.09	0.3652	-1331.09	0.1053	0.787	.689-.959

The collective interpretation of multiple fit indices and indices of classification quality are used to guide the selection of the most appropriate multi-profile model. Interpretation of each fit index has been summarized previously [26]. AIC Akaike Information Criteria, SSA BIC sample size adjusted Bayesian Information Criteria, LMR-LRT Lo-Mendell-Rubin Likelihood Ratio Test, BLRT Bootstrap Likelihood Ratio Test. AIC, SSA BIC, LMR-LRT and BLRT are fit indices. Entropy and Classification probabilities are indices of classification quality

ISSN: 1471-2431