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. Author manuscript; available in PMC: 2015 Dec 1.
Published in final edited form as: J Behav Med. 2014 Feb 21;37(6):1091–1101. doi: 10.1007/s10865-014-9560-y

Table 2.

Conditional Growth Curve Models

Model Sexual Experience Number of Partners Inconsistent Condom Use
Model Fit Statistics
χ2 (df) 10.70 (19) 14.30 (18) 14.30 (19)
p-value .93 .71 .27
CFI 1.00 1.00 .99
TLI 1.00 1.03 .98
RMSEA .00 .00 .03
WRMR .20 .05 .04
Path coefficients β (p-value) β (p-value) β (p-value)
Intercept (T1) on CEV .23 (.009) .26 (.000) .20 (.001)
Intercept (T2) on CEV .23 (.007) .22 (.002) .16 (.039)
Intercept (T3) on CEV .23 (.008) .19 (.015) .14 (.104)
Intercept (T4) on CEV .23 (.020) .18 (.020) .16 (.057)
Intercept (T5) on CEV .23 (.065) .19 (.012) .22 (.010)
Intercept (T6) on CEV .21 (.183) .19 (.025) .27 (.003)
Slope (T1) on CEV −.19 (.256) −.03 (.803) −.09 (.322)
Slope (T2) on CEV −.19 (.256) −.03 (.772) −.05 (.559)
Slope (T3) on CEV −.19 (.256) −.03 (.752) .06 (.509)
Slope (T4) on CEV −.19 (.256) −.01 (.887) .18 (.081)
Slope (T5) on CEV −.19 (.256) −.001 (.994) .18 (.071)
Slope (T6) on CEV −.19 (.256) .01 (.961) .18 (.080)
Quadratic on CEV NA .02 (.878) .15 (.135)
Intercept (T1) on Age .47 (.000) .21 (.027) .31 (.000)
Intercept (T2) on Age .45 (.000) .21 (.027) .36 (.000)
Intercept (T3) on Age .42 (.000) .19 (.049) .32 (.000)
Intercept (T4) on Age .38 (.003) .18 (.062) .27 (.001)
Intercept (T5) on Age .32 (.019) .16 (.070) .19 (.026)
Intercept (T6) on Age .23 (.196) .11 (.208) .07 (.395)
Slope (T1) on Age −.54 (.003) −.04 (.730) .09 (.374)
Slope (T2) on Age −.54 (.003) −.02 (.846) .05 (.605)
Slope (T3) on Age −.54 (.003) −.02 (.783) −.06 (.507)
Slope (T4) on Age −.54 (.003) −.07 (.429) −.18 (.019)
Slope (T5) on Age −.54 (.003) −.08 (.451) −.19 (.037)
Slope (T6) on Age −.54 (.003) −.07 (.483) −.18 (.062)
Quadratic on Age NA −.06 (.577) −.15 (.154)

NOTE: χ2 = chi-square statistic reflecting overall model fit (p > .05 indicates a good fit); df = degrees of freedom; CFI = Comparative Fit Index (≥ .90 indicates a good fit); TFI = Tucker-Lewis Index (≥ .90 indicates a good fit); RMSEA = Root Mean Square Error of Approximation (≤ .05 is considered a very close fit; .05 – .10 is considered a moderate fit); WRMR = Weighted Root-Mean-Square Residual (used for binary outcomes, ≤ .9 is considered a good fit); SRMR = Standardized Root-Mean-Square Residual (used for continuous outcomes, ≤ .08 is considered a good fit). β = standardized regression coefficient; T = Wave 1; T2 = Wave 2; T3 = Wave 3; T4 = Wave 4; T5 = Wave 5; T6 = Wave 6; CEV = childhood exposure to violence. Models are tested with the intercept set at each time point. Note that in quadratic models, the slope also changes over time, whereas the slope is constant in the probit model.