Table 5.

Parameter estimates for the two class regression mixture model (with and without the C on x path included) when the true underlying relationship between x and y is a piecewise relationship

	True values		N=100,000				N=2,000
			C on x path omitted		C on x path included		C on x path omitted		C on x path included
	Class 1	Class 2	Class 1	Class 2	Class 1	Class 2	Class 1	Class 2	Class 1	Class 2
Class Proportion	.50	.50	.57	.43	.50	.50	.58	.42	.49	.51
Y on X	.2	.7	.285 (.007)	.773 (.013)	.202 (.007)	.713 (.005)	.284 (.049)	.801 (.079)	.240 (.050)	.672 (.040)
Intercept Y	0	0	.496 (.012)	−.226 (.015)	−.002 (.007)	−.009 (.005)	.431 (.063)	−.260 (.091)	−.030 (.052)	.003 (.036)
Residual Y	.96	.51	.584 (.005)	.560 (.007)	.954 (.006)	.507 (.003)	.582 (.034)	.597 (.047)	.982 (.042)	.511 (.021)
Class Intercept/Mean	0		.279 (.068)		−89.459 (.698)		−.333 (.386)		−228.001 (27.984)
C on X	∞		na		not estimable		na		Not estimable

Explanation of terms: Class proportions refer to the proportion of cases estimated in each class; Y on x refers to the regression coefficient for each class; Intercept Y refers to the intercept for the regression of Y on x for the class; Residual Y refers to the residual associated with the regression of Y on x for the class; Class Intercept/Mean refers to the intercept from regressing C on x (logistic regression with one class as the reference group) or the class mean when C on x is excluded; C on x refers to the regression of class membership on x (logistic regression). N=sample size, na=not estimated.