Mixed methods latest
- 1. MIXED METHODS By, Dr. Johan @ Eddy Luaran
- 2. DEFINITION Mixed methods research combines quantitative and qualitative approaches by including both quantitative and qualitative data in a single study.
- 3. PURPOSE To build on the synergy and strength that exists between quantitative and qualitative research methods. To understand a phenomenon more fully than is possible using either quantitative or qualitative methods alone.
- 4. “Mixed methods research allows the use of both words and numbers to obtain a better understanding” (Caracelli & Greene, 1993). “Results can be generalized through the use of quantitative data while providing individual voices through the use of qualitative data” (Tashakkori & Teddlie, 2003). “mixed methods research creates a deeper understanding of research by using the strengths of qualitative and quantitative research to inform both” (Creswell & Plano Clark, 2007)
- 5. Deductive approach Concerned with objective reality that is there to be discovered. Establishing cause-effect relationship. Identify hypotheses to test. Inductive approach Focus on interpreting their participants’ perspectives. Describing and understanding relationships. Work with guiding hypothesis and allow specific focus to emerge as a study progresses. CHA R A CTER ISTICS OF QUA NTITA TIVE & QUALITATIVE RESEARCH QUANTITATIVE QUALITATIVE
- 6. TYPES OF MIXED METHODS RESEARCH DESIGN a) QUAL-quan model b) QUAN-qual model c) QUAN-QUAL model
- 7. a) QUAL - Quan Model Also known as exploratory mixed methods design. Qualitative data are collected first and are more heavily weighted than quantitative data. In the first phase of this model, observation and open-ended interviews with individuals or groups are conducted and concepts and potential hypotheses are identified.
- 8. In the second phase , variables are identified from concepts derived from the qualitative analysis and hypotheses are tested with quantitative techniques. When qualitative methods are dominant, qualitative researchers may decide to include survey, census, and Likert- scale data along with narrative data. The validity of the qualitative results can be enhanced by the quantitative results.
- 9. (b) QUAN-Qual Model Also known as the explanatory mixed methods design. Quantitative data are collected first and are more heavily weighted than qualitative data In the first study or phase, the researcher formulates a hypothesis, collects quantitative data and conducts data analysis.
- 10. The findings of the quantitative study determine the type of data collected in a second study of phase that includes qualitative data collection, analysis and interpretation. The researcher can then use the qualitative analysis and interpretation to help explain or elaborate on the quantitative results.
- 11. (c) QUAN-QUAL Model Also known as the triangulation mixed methods design. In this model, quantitative and qualitative data are equally weighted and are collected concurrently throughout the same study-the data are not collected in separate studies or distinct phases, as in the other 2 methods..
- 12. one of the most difficult aspects of any research endeavor is the analysis of data. Creswell developed a comprehensive overview of mixed methods design data analysis & interpretation procedures (pg 487, Table 19.3) There were some examples of analytic & interpretation procedures of types of mixed methods designs ( triangulation, explanatory & explanatory)
- 13. Example 1. Quantifying qualitative data: Quanlitative data are coded, codes are assigned numbers, and the numbers of times codes appear are recorded as numeric data. Quantitative data are descriptively analyzed for frequency of occurrence. The two data sets are compared. Set of Frequency of Questionnaires Occurrence Interview Codes that counted for frequencies QUAN data collection QUAL data collection QUAN data analysis QUAL Data analysis Compare & Interrelate two QUAN data sets Interpretation QUAN+QUAL
- 14. Example 2. Quantifying quantitative data: Quantitative data from questionnaires are factor-analyzed. These factors then become themes and then are compared with themes analyzed from qualitative data. Observation Identify theme Questionnaires Factor QUAL data collection QUAN data collection QUAN data analysis Compare & Interrelate Data sets QUAL data analysis
- 15. Example 1. Explaining results: Conduct a quantitative survey to identify how or more groups compare on a variables. Follow up with qualitative interviews to explore the reasons why these differences were found Interview QUAN data collection QUAN result qual data analysis qual data collection Interpretation QUAN qual Identify result for follow up QUAN data analysis qual result
- 16. Example 1. Developing an instruments: Obtain themes & specific statements from individuals that support the themes. In the next phrase, use these themes & statements to create scales & items as a questionnaire. Alternatively, look for existing instruments that can be modified to fit the themes & statements found in the qualitative exploratory phase of the study. After developing the instruments, test it out with the sample of population. Develop Instrument Interpretation QUAL quan quan data collection quan result quan data analysis QUAL result QUAL data analysis QUAL data collection
- 17. Characteristics that help to identify a study as having a mixed method design: The study title The data collection section The purpose statement or the research questions The researchers indicates the preference given to qualitative or quantitative data collection The researchers indicates the sequence in which qualitative , quantitative or both types of data were collected The researchers describes how data were analyzed using both quantitative and qualitative strategies.
- 18. Evaluating a mixed methods study : A mixed method study can be evaluated by answering questions related to ; the use of at least one qualitative & one quantitative research method the rational for using a mixed methods research design the priority & sequence given to qualitative & quantitative data collection The use of qualitative & quantitative research questions and matching data collection techniques The use of appropriate data analysis techniques for mixed designs