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. Author manuscript; available in PMC: 2018 Aug 1.
Published in final edited form as: Exp Clin Psychopharmacol. 2017 Jun 19;25(4):281–294. doi: 10.1037/pha0000131

Table 4.

Unstandardized Indirect Effects for Exogenous Variables Predicting Marijuana Outcomes

Variables/Path b SE 95% CI
Sensitivity to Punishment (SP)
  SP → ALS → T1 Problem Intensity 0.06 0.03 [0.006, 0.129]
  SP → PC → T1 Likelihood of Abstaining −0.17 0.05 [−0.288, −0.072]
  SP → PC → T1 Use Intensity 0.09 0.03 [0.033, 0.151]
  SP → PC → T1 Problem Intensity 0.06 0.02 [0.015, 0.098]
  SP → PC → T2 Likelihood of Abstaining −0.16 0.05 [−0.260, −0.066]
  SP → PC → T2 Use Intensity −0.01 0.02 [−0.053, 0.032]
Sensitivity to Reward (SR)
  SR → ALS → T1 Problem Intensity 0.02 0.01 [0.003, 0.054]
  SR → PC → T1 Likelihood of Abstaining −0.25 0.07 [−0.418, −0.117]
  SR → PC → T1 Use Intensity 0.13 0.04 [0.048, 0.226]
  SR → PC → T1 Problem Intensity 0.08 0.03 [0.024, 0.148]
  SR → PC → T2 Likelihood of Abstaining −0.23 0.07 [−0.369, −0.081]
  SR → PC → T2 Use Intensity −0.02 0.03 [−0.083, 0.043]
Total Effects
  SP → T1 Likelihood of Abstaining 0.37 0.10 [0.190, 0.608]
  SP → T1 Use Intensity 0.06 0.07 [−0.113, 0.183]
  SR → T1 Likelihood of Abstaining −0.76 0.12 [−1.082, −0.552]
  SR → T1 Use Intensity 0.00 0.07 [−0.153, 0.158]

Note. ALS = Affect Lability; PC = Poor Control; SR = Sensitivity to Reward; SP = Sensitivity to Punishment; Intensity = Count Portion of Zero-Inflated Negative Binomial (ZINB) Count Model; Likelihood = Inflation Portion of ZINB Count Model. The inflation portion of the ZINB count model reflects the likelihood of obtaining a zero (i.e., abstaining or having no problems, respectively). Therefore, a positive value represents an increased likelihood of obtaining a zero and a negative value indicates a decrease likelihood of obtaining a zero value (i.e. using). Indirect and total effects were calculated using bias corrected bootstrapped confidence intervals. Significance is represented by a confidence interval that does not contain zero. Total effect represent the effect of one exogenous variable at the mean level of the other.