Academic and demographic variables as predictors of gang activity in school

A two-group predictive discriminant analysis was used to develop a model to predict youth gang activity among students in an urban school district in south central United States. The predictors were selected from age, race, gender, grade repeats, reading comprehension achievement test scores, and changes in school and school district (uprootedness). Data were obtained from elementary school records of 285 grade nine students (151 male and 134 female) in two junior high schools. Ethnic minorities comprised 75.4% of the sample. Gang involvement data were provided by the school district security department. Data were analyzed using SPSS-X and a FORTRAN computer program by Morris and Meshbane (1995). All possible subsets of predictor variables were examined using leave-one-out cross-validation accuracy estimates. Although no models classified both gang and nongang students with greater accuracy than proportional chance expectations, a model consisting of gender, grade repeats, and school and school district changes (uprootedness) yielded significant classification accuracy for gang students, (z = 12.07, p <.05).