Data analyses of people nested in groups has evolved over the past 2 decades. Group members interact with each other, they share common experiences within their group that may be different across groups, and each group may be affected by different compositions and histories. These factors make groups and group research exciting, but they also complicate the analyses of grouped data. This special issue of Group Dynamics: Theory, Research, and Practice gathers 8 articles that are structured as tutorials for conducting statistical analyses that are appropriate to capture the unique and emergent properties of groups. The articles are geared toward new researchers, students, and interested readers who want to learn to conduct or evaluate a study using these statistical methods. Statistical methods reviewed in this special issue include the latent group model, multilevel methods to assess between and within-leader variance, multilevel confirmatory factor analysis, the relational event model, the social relations model, sequential analysis, recurrence analysis, and statistical discourse analysis. Each article presents the main concepts, a running example, instructions on how to run the analyses and interpret outputs, suggestions on when to use the technique, and common problems that may be encountered when using these methods. Most of the articles provide equations that are concretely explained, computer syntax, example data, annotated bibliographies, and website links. The articles in this special section represent a sampling of the state of the art in statistical methodology for group psychology and group psychotherapy research.