Data analytic methods for the analysis of multilevel questions

Comparisons of the statistical procedures used in the multilevel data analyses in the previous articles of this special issue are compared and recommendations for their use are presented.

Abstract

Researchers investigating organizations and leadership in particular are increasingly being called upon to theorize multilevel models and to utilize multilevel data analytic techniques. However, the literature provides relatively little guidance for researchers to identify which of the multilevel methodologies are appropriate for their particular questions. In this final article, the statistical procedures used in the multilevel data analyses in the previous articles of this special issue are compared. Specifically, intraclass correlation coefficients (ICCs), rwg(j), hierarchical linear modeling (HLM), within- and between-analysis (WABA), and random group resampling (RGR) are examined and their results and conclusions discussed. Following comparisons of these methods, recommendations for their use are presented.