TABLE 8.

Specificity

	MD = 1.5		MD = 3.0
	TAX	FMM	TAX	FMM
π1 = .5
LCA5	0.72	0.71	0.74	0.93
LCA10	0.69	0.69	0.86	0.92
1F	0.73	0.77	0.93	0.93
2Fcl	0.74	0.68	0.93	0.93
2Fss	0.75	0.70	0.93	0.93
π1 = .95
LCA5	0.60	0.85	0.75	0.99
LCA10	0.48	0.89	0.86	0.99
1F	0.78	0.97	0.94	0.99
2Fcl	0.76	0.95	0.93	0.99
2Fss	0.75	0.92	0.91	0.99

Note. Average specificity of taxometric procedures (TAX) and the factor mixture model (FMM). Specificity is defined as the proportion of subjects in the first (majority) class correctly assigned to the first class. Table entries are conditional on the detection rates of the two-class structure as summarized in Table 6, which are close to zero for taxometric procedures for some conditions. Results based on fewer than six data sets are presented in italics. MD = Mahalanobis distance; LCA5 = latent class data with 5 indicators; LCA10 = latent class data with 10 indicators; 1F = one-factor data with 10 indicators; 2Fcl = two-factor data with cross-loadings with 10 indicators; 2Fss = two-factor data with simple structure with 10 indicators; π₁ = proportion of subjects in the first class where π₂ = 1 — π₁.