Triangulation using a meta-matrix
Background and significance. Quantitative and qualitative data analysis are often undertaken as separate enterprises, as they emerge from differing philosophies of science and methodologies for data collection, management and analysis. Quantitative data analysis is sometimes seen in philosophic and methodologic conflict with a naturalistic, human science perspective of science. Researchers interested in data from both realms often rely on triangulation procedures, in which each is considered from its representative lens. Results are then projected out into a common area where data are melded and discussed. The purpose of this paper is to introduce the meta-matrix as a tool for triangulation in nursing research and to demonstrate its usefulness in an exemplar case.
Design/methods. The exploratory nature of a recent study led to the decision to manage triangulation using an emerging methodology, thereby allowing consideration of all data simultaneously through the use of a meta-matrix. Discussion of the meta-matrix as a method is presented.
Findings. Use of the meta-matrix facilitated data analysis and allowed pattern recognition across data sets. Discovery of several unexpected relationships deepened understanding of the results and assisted in identifying questions for further research.
Conclusions/implications. The meta-matrix method provides a useful alternative approach for secondary-level data analysis in mixed-methods research.