Hey, I am currently writing a paper about risks in software implementations. For that I am using an employee survey (qual + quant) plus qualitative interviews (semi-standardized). Both research methods use qual and quant questions. The evaluation of the survey will take place with graphs, means and hypothetical tests, and the evaluation of the interviews will be inductive as well as deductive. The reasoning will include a mixture of both results.
In that sense - is it correct to use the integrated mixed model design?
Warm thanks in advance!
What you describe sounds more like two separate sets of results. How do you plan to integrate them? (Note that integration is often a problem in "complementary" or "parallel convergent" designs.)
Yes you are right, there will be two sets of results. Consequently it won't be the integrated mixed model design, am I correct? Much more a Mixed Method?
Not quite sure how it is named but I plan to integrate both results in the discussion on the basis of confirmation and contradiction.
Complementarity is undoubtedly the most common design in mixed methods research, and the degree of integration is the key to how well it is accomplished. Setting the two sets of results up so that they can be integrated during the Results section is preferable to presenting them separately and then making the comparison in the Discussion section. But if your design doesn't isn't compatible with that format, then a thorough discussion of "confirmation and contradiction" would still be more than most complementary mixed methods studies achieve.
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