. Author manuscript; available in PMC: 2014 Jan 7.

Published in final edited form as: J Aging Health. 2013 May 1;25(4):10.1177/0898264313484058. doi: 10.1177/0898264313484058

Table 2.

Unconditional and Conditional Linear Latent Growth Models of Alcohol Consumption and Frequency of Drinking.

	Alcohol Consumption				Drinking Frequency
	Binary		Continuous		Binary		Continuous
	IU	SU	IY	SY	IU	SU	IY	SY
Unconditional linear growth models

Initial growth factor mean	−0.13	−0.17^**	1.02^**	−0.03^**	1.96^**	−0.09^**	1.09^**	0.06^**
Variance of growth factor mean	24.82^**	0.00	1.83^**	0.03^**	20.98	0.00	6.06^**	0.08^**
Model fit
Log likelihood	−31, 432.6				−28, 792.9
BIC	62, 985.6				57, 706.4

Conditional linear growth models	IU_C	SU_C	IY_C	SY_C	IU_C	SU_C	IY_C	SY_C
Predictors
Number of painful medical conditions
Initial growth factor mean	−0.28^**	−0.00	−0.02	−0.00	−0.32^**	−0.01	−0.14^**	−0.02^*
Variance of growth factor mean	21.85^**	0.00	1.47^**	0.01^**	17.58^**	0.00	5.16^**	0.02^**
Model fit
Log likelihood	−30, 894.6				−28, 411.0
BIC	62, 116.1				57, 148.9
Severity of pain
Initial growth factor mean	−0.46^**	0.00	−0.01	−0.01^*	−0.43^**	0.00	−0.10^*	−0.02^*
Variance of growth factor mean	21.76^**	0.00	1.47^**	0.01^**	17.54^**	0.00	5.18^**	0.02^**
Model fit
Log likelihood	−30, 888.3				−28, 408.7
BIC	62, 103.5				57, 144.3
Pain interference
Initial growth factor mean	−1.26^**	0.03	−0.12	−0.01	−1.16^**	0.02	−0.31^**	−0.04^*
Variance of growth factor mean	21.73^**	0.00	1.46^**	0.01^**	17.55^**	0.00	5.17^**	0.02^**
Model fit
Log likelihood	−30, 878.3				−28, 406.5
BIC	62, 083.4				57, 139.9

Notes:

p < .05.

^**

p < .01.

BIC = Bayesian information criterion; IU = threshold for binary part of model, = likelihood of 0 → 1 = 1−[1/1+exp (−threshold value)]; SU = slope for the binary part of model; IY = intercept for continuous part of model; SY = slope for the continuous part of model; IU_c = intercept coefficient for binary part of model; SU_c = slope coefficient for binary part of model; IY_c = intercept coefficient for continuous part of model; SY_c = slope coefficient for continuous part of model. SU variance fixed at zero. Conditional growth models control for age, gender, race, illness severity, and number of medications. Residual variances for Alcohol Consumption growth models range = 0.53 to 0.73**; residual variance for Drinking Frequency growth models range = 1.37 to 2.06**.