Studies on cyberbullying are replete with questions about whether certain risk or protective factors are likely to predict cyberbullying outcomes such as cybervictimization. Such questions can often be reframed in terms of moderation effects, or hypotheses about how the effect of a predictor variable on an outcome variable depends on the value of a moderator variable. Demonstrating how questions about moderation effects are conventionally tested using the dataset from the Teens and Parents survey conducted by the Pew Research Centre’s Internet and American Life Project, the current study found two sets of significant moderation effects that could be interpreted to mean that the predictive relationship between traditional victimization and cybervictimization depend on the teenager’s intensity of SNS use and gender. A secondary purpose of this paper is to extend the conventional analytic approach in the form of an R package that provide researchers with methods – based on the pick-a-point technique and the Johnson-Neyman technique – which they can use to probe moderation effects they find significant in their research projects. Empirical illustrations with the cyberbullying dataset are provided throughout to demonstrate the use of this R package.