Make an argument for using a mixed methods approach. Consider the reasons that this particular study needs a mixed research design. For instance, how would using mixed methods advance knowledge in your field? You may also consider your own personal reasons for conducting the study. Write your hypothesis to reflect the use of mixed methods. Create an over-arching question that supports this. Formulate sub-questions that will be explored using qualitative and quantitative methodologies respectively.
Select a specific mixed methods research design. Decide if a preexisting design would be best or if you need to develop your own research design for your specific study. Consider the different categories of mixed methods design. In an explanatory design, quantitative data are collected first, followed by qualitative data. This allows the numerical data to be compared to the qualitative data that follows. An exploratory design collects qualitative data first, which will explore the given area and possibly narrow the question posed by the quantitative portion of the study. Consider also the use of triangulation, in which quantitative and qualitative data are collected simultaneously in order to provide a more thorough set of data.
Choose your data collection strategies. This will be informed by your research questions and design. Select units of analysis. Will you be collecting data from individuals, cases or groups? In what settings will you collect data? For instance, will you use mail-in or Internet surveys or use college students in a classroom setting? Keep in mind that you will need to plan how you will collect data for both the quantitative and qualitative phases of your study.
Utilize both qualitative and quantitative methods of analysis. Choose whether you want to analyze the data at the same time or analyze one method first in order to inform the other. Follow the same basic process of data analysis as you would in any study --- reduce or clean data, display data in an organized form for easy reference, transform data (for instance code and simplify) and analyze each type of data using the appropriate methods. Integrate your data. Combine qualitative and quantitative data into a data set or sets which can be looked at separately or as a whole in order to draw conclusions about the study.