In order to identify factors associated with recidivism for individuals exiting five-month long, post-prison residential substance abuse treatment programs, researchers collected data from a sample of 897 individuals at the time they entered the substance abuse programs along wth department of justice recidivism data covering the results of preliminary bivariate analyses between various factors and recidivism, the researchers decided to run an analysis using a multivariate model. The model incorporated the following variables: Substance abuse problem severity at time of admission into program (measured using a continuous 100-point scale with higher scores indicating higher levels of addiction); Sex (1 = male; 0 = female); Primary drug of choice (1 = methamphetamine; 2 = heroin; 3 = cocaine/ crack; 4 = marijuana; 5 = alcohol; 6 = other and Five year recidivism outcome (measured using days to re-arrest - 1826 days given if they were not re-arrested). To conduct their analysis, the researchers decided to run the model using __135____. Prior to running the analysis, the researchers had to recode the primary drug of choice variable into ___136___ dummy variable(s). In order to assess whether or not the full model was significantly associated with recidivism, the researchers looked at the p-value of .047. The researchers concluded that the overall model was __137____. The ___138____ value of 0.40 indicates that we have explained 40% of the variability in the dependent variable with our model. To determine whether initial substance abuse problem severity was significantly associated with recidivism after controlling for the other factors in the model, the researchers reported the ___139____ for the substance abuse problem severity variable and its associated p-value. 135. a. t-test b. ANOVA c. logistic regression d. Linear regression 136. a. One b. Two c. Five d. Six 137. a. Statistically significant b. Not significant c. Faulty d. Substantively sound 138. a. Chi-square b. Pearson's r c. R square d. T statistic 139. a. Chi-square b. ANOVA c. Standardized coefficient (beta) d. t statistic