Table 1.

Bayesian Information Criterion (BIC) Values for Alternative Models

Model	Cluster Characteristics				Number of Clusters
	Distribution	Shape	Volume	Orientation	1	2	3	4	5	6	7	8	9
1	ellipsoidal	varying	varying	varying	−2861	−2825	−2886	−2952	--	--	−3009	−3047	−3122
2	ellipsoidal	equal	equal	varying	−2861	−2829	−2855	−2890	−2911	−2968	−2967	−3009	−3025
3	ellipsoidal	equal	varying	varying	−2861	−2834	−2872	−2884	−2928	−2932	−2982	−3012	−3095
4	diagonal	varying	varying	equal	−2931	−2862	−2855	−2886	--	--	--	--	--
5	diagonal	varying	equal	varying	−2931	−2870	−2863	−2871	−2889	−2912	−2904	--	--
6	diagonal	equal	varying	varying	−2931	−2883	−2861	−2848	−2852	−2888	−2895	−2869	−2882
7	diagonal	equal	equal	varying	−2931	−2883	−2853	−2844	−2859	−2854	−2875	−2882	−2895
8	ellipsoidal	equal	equal	equal	−2861	−2884	−2857	−2839	−2860	−2872	−2878	−2900	−2899
9	spherical	equal	varying	varying	−4608	−4433	−4233	−4146	−4031	−3975	−3926	−3883	−3849
10	spherical	varying	equal	varying	−4608	−4470	−4281	−4186	−4134	−4106	−4005	−3990	−3995

Note. Values represent BIC values; smaller negative values indicate better fit. The two best-fitting models are in bold. Cluster characteristics include Shape, Volume, and Orientation and refer to the geometric characteristics of the clusters’ distributional shape in multivariate space. Dashes in the row for Model 1 indicates that an orientation parameter could not be estimated, as there were no off-diagonal elements. Dashes in the rows for Models 4 and 5 indicate that the sample was too small to estimate the fit of the Model beyond 4 or 7 clusters.