Hi Stephan,

Thank you for your response. I agree with your comment on the need for separate analyses of qualitative and quantitative data before data integration in convergent designs. I am actually after a possibility to build a matrix, which will help to compare and corroborate the findings from both types of data - the integration that is necessary in convergent designs. In the Journal of Mixed Methods Research, scholars often mention that such a matrix could be helpful, and I am interested now in a praxis of creating it in the most efficient way possible. I understand from your response and experience now that MAXQDA would not be useful here. I appreciate your comment and will look further now.

Regards,

Anna   

Anna,

I think Stephan's reply was quite reasonable and that your idea to create a matrix is a useful approach to this kind of design. I myself am particularly interested in the idea of using a matrix or equivalent for comparing qualitative and quantitative results, but I can't recall any matrix-based articles that appeared in the Journal of Mixed Methods Research. So if you have a reference you could share, please let me know.

Here is one example of an article I have located that explicitly used a matrix-comparison strategy to examine convergence.

D. Cline et al., Factors Influencing RNs’ Perceptions of Quality Geriatric Care in Rural Hospitals. Western Journal of Nursing Research, published online Dec. 2013.

Hello David, 

Thank you for your helpful post - the article in the WJNR is very informative and useful. I like the matrix figure that the authors have provided to illustrate how they actually compared the data against different constructs. I am thinking to adopt this strategy in my study.   

To response to your comment, I was not able to locate really helpful practical examples of application of integrative matrices so far in the Journal of Mixed Methods Research, although there is a limited number of quite good conceptual papers. Here is the one I could suggest by Castro et al. in 2010. 

Felipe González Castro, Joshua G. Kellison, Stephen J. Boyd, and Albert Kopak. A methodology for conducting integrative mixed methods research and data analyses.

Journal of Mixed Methods Research, October 2010; vol. 4, 4: pp. 342-360

I just looked over the Castro et al. article and it seems to me to be an elaborate quantification of strictly qualitative data. They do show a diagram for integration of "parallel" tracks for qualitative and quantitative data, but as far as I can tell, they alternated between looking at essentially the same data qualitatively and quantitatively.

To me, the underlying problem with conducting qualitative and quantitative studies in parallel, and then comparing them at the end, is the issue of potential divergence when you do the ultimate comparison. On the one hand, if the results are indeed mutually informative, then this is a useful kind of deisgn. On the other hand, if the two methods end of targeting different aspects of research topic, then the divergence will be problematic.

Here is another article that might be helpful. Although the authors are comparing two different qualitative methods (rather than mixed methods), they did so by directly comparing the two sets of results to assess the degree of convergence.

T. Farmer et al. 2006 Developing and Implementing a Triangulation Protocol for Qualitative Health Research, Qualitative Health Research, 16:377-394.

Hello David, Measuring the degree of divergence makes so much sense. I am integrating this method into my design. Thank you! Kim