I am looking for methods to analyze participants perception on future outcomes collected through a survey followed by qualitative data collected through focus groups. How do I combine data from these two sources and conduct a mixed methodology (Qualitative + Quantitative)? Is there any other better approach than the mixed methodology?
Thank you in advance for reading my inquiry.
Whel! In my understanding you highlighting in your question a triangular approach or mix method approach. Since you're most interested in future forecasting. Regression is the key in analysis according to given scenario. Further, regression is a huge subject; principle component regression might help you to break your data in different component according to data nomenclature specification. You'll be in good position to get your answer according to your work. However, there are other avenues to work it on.
CANNOT COMBINE. The data came from two distinct sources that generated different types of data. The survey gives you quantitative data, i.e. Likert scale or other type of scale, and the interview is qualitative data that requires codings and scoring (1,0). The survey is analyzed under continuous probability and the interview under discrete probability for purpose of hypothesis testing.
SUPPLEMENTAL REPORT. While the survey data can be analyzed in a straight forward manner with statistical tools, the interviews may be reported as a supplement or anecdotal since it is difficult to show scientific objectivity.
HYPOTHESIS TESTING. At the end, it comes down to hypothesis testing. By convention, hypo testing is accomplished through statistical tests. Quantitative and qualitative data should be tested separately then compare the outcome.
Hello Farah
You can analyze the quantitative and qualitative data separately using appropriate analysis techniques. There is no need to combine the data as such; however, you can definitely see how the results obtained from quantitative and qualitative analysis are converging i.e. both indicating similar patterns of behaviour or attribute being measured among the participants. Using mixed method allows you to confirm what you get through one form of data; thus, triangulation of findings.
You should adopt a new qualitative framework for collecting and analyzing focus group data. First, identify types of data that can be collected during focus groups. Second, identify the qualitative data analysis techniques best suited for analyzing these data. Third, introduce what a micro-interlocutor analysis, wherein meticulous information about which participant responds to each question, the order in which each participant responds, response characteristics, the nonverbal communication used, and the like is collected, analyzed, and interpreted.
Hi Dr Farah Naz . It clcan be analyzed via constant comparison analysis, especially when there are multiple focus groups within the same study, which, as noted previously, allows the focus group researcher to assess saturation in general and across-group saturation in particular. See the link: Article A Qualitative Framework for Collecting and Analyzing Data in...
Also, see the following link: https://www.surveymonkey.com/mp/how-to-analyze-survey-data/
Kindly see also the following link: https://upstream.consulting/grant-readiness/how-to-analyze-focus-group-data
Hi Farah!
In my opinion, you need to be clear about the design of your research, I think it is a mixed research sequences (QUAN-QUAL), having clarity of it, the quantitative would serve you to set up your focus group and choose your participants or structure the way to look at the qualitative discourses to deepen in some areas. For example, with the quantitative you will have a general view of the population and with the qualitative you can go deeper into some logics that catch your attention, either by majority or minority.
When you make that constant comparison, you generate depth and richness in your analysis, if you do it separately, it would no longer be a mixed method and it would be two separate analyses, therefore the type of "mixed" design will guide you in the way you generate your hypotheses and in the way you should look at your data to analyze.
Hello Farah, I will recommend inductive thematic analysis or content analysis qualitative data (FGD's). For a quantitative survey data, statistical regression analysis will be favourable in forecasting or for testing hypothesis.
The classic mixed methods design for this combination is an explanatory sequential design (QUAN --> qual) where you use the follow-up qualitative study to help you understand the quantitative results.
The advantage of this design over your proposed QUAN + qual is that it uses the sequential nature of the data collection to strengthen what you would obtain from the quantitative study along.
I would suggest that let the qualitative be analysed using content analysis and for quantitative use also analytical methods as required too for exaple, u can use STATA, SPSS or excel.
In other words I think there is no need to combine systems of analysis.
If you do want to combine the analyses, almost all of the qualitative data analysis programs now include what they can a "mixed methods" mode. This basically consists of using participant ID numbers to export codes in a spreadsheet format. This will results in a series of dummy variables (present/absent) for each participant.
Dear Dr. Farah Naz
If you want to combine analyses, almost all qualitative data analysis systems now provide a "mixed methods" option. This entails exporting codes in a spreadsheet format using participant ID numbers. Consequently, each participant will have a set of dummy variables (present/absent).
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