Journal Articles
Abstract:
Twenty years ago, hierarchical regression and analysis of covariance were the established statistical methods commonly found in clinical psychology research studies. At present, these methods have largely given way to hierarchical linear models (HLM) and structural equation models (SEM), which are used in many—if not most—research studies. For more than two decades, ABCT has attempted to meet the ever-widening gap by offering a series of workshops during its annual conference that focus on topics related to statistics and research methodology. The primary motivation for applied researchers to stay on top of advances made in statistics and research methodology is that as our field matures, we are asking increasingly complex questions about human behavior that require more sophisticated research designs and statistical techniques. Here we present findings from this survey, address a frequent misunderstanding about AMASS sessions, and introduce the creation of a new Special Interest Group (SIG) devoted to Clinical Research Methods and Statistics. Results show that respondents expressed the most interest for workshops focused on HLM for continuous and nonnormal outcomes, power analyses, longitudinal mediation, missing data, and SEM approaches. (PsycINFO Database Record (c) 2016 APA, all rights reserved)