An illustration of item homogeneity scaling and multilevel analysis techniques in the evaluation of drug prevention programs.
Many reports of successful school-based intervention programs can be criticized for their choice of a unit of analysis and for the neglect of measurement errors. This article is an illustration of how different conclusions can be reached from different choices of units of analyses and/or of different treatment of the data. This is done by a reanalysis of a well-reported data set. The data is thoroughly taken apart, using different statistical techniques. The result of the analyses shows that earlier reported effects of a normative school-based drug prevention program were not found. The subsequent search for moderator effects of the same program, such as a lowering effect on the relationship between the pre- and posttest or on the relationship between respondents' use and the use of their friends, was not successful either. It is concluded that the null hypothesis of zero effects should be retained. More successful was a search for individual characteristics that show significant relationships with respondents' alcohol use. Among them was the abuse of alcohol by adults in respondents' direct social environment and the use of friends.
Kreft
I G
IG
California State University, Los Angeles, USA.
D000293:Adolescent; D000328:Adult; D000704:Analysis of Variance; D002648:Child; D005260:Female; D006801:Humans; D016014:Linear Models; D008297:Male; D015233:Models, Statistical; D015999:Multivariate Analysis; D015397:Program Evaluation / Q000379:methods*; D012680:Sensitivity and Specificity; D013223:Statistics as Topic; D019966:Substance-Related Disorders / Q000517:prevention & control*; D014481:United States