Toward a Metaframework for Conducting Mixed-Methods Power Analyses

• In Event: Data Analysis Issues in Mixed Methods Research

Abstract

Due to a dearth of literature on the topic of mixed methods sampling designs and the high incidence of mixed researchers who struggle with this topic, the purpose of this paper is to propose a meta-framework for mixed methods power analyses (MMPA). We define MMPA as the appropriate selection of sampling design (e.g., sampling scheme [e.g., stratified random sampling], sample size [of people, words, text, observations, events, incidents, activities, experiences, or any other object of study], subsample size[s], group size[s] per approach, number of observational units per participant) in order to obtain meta-inferences consistent with the study’s generalization goal(s). Thus, the goal of conducting MMPA is to attain interpretive consistency in order to enhance the rigor of mixed methods studies.

Authors

• Julie Anne Corrigan, University of Ottawa

• Anthony J. Onwuegbuzie, Sam Houston State University