Abstract
In this article, we review current state-of-the art software enabling statisticians to apply design-based, model-based, and so-called “hybrid” approaches to the analysis of complex sample survey data. We present brief overviews of the similarities and differences between these alternative approaches, and then focus on software tools that are presently available for implementing each approach. We conclude with a summary of directions for future software development in this area.