Qualitative Data Analysis

1. Qualitative Data Analysis

2. Step 1: Determining Questions • “Start-up” questions are general questions that help to frame the initial qualitative research project. • Emergent questions develop during the research process. • Both “start-up” and “emergent” questions guide qualitative data analysis.

3. Step 2: Unitizing Textual Data • Textual data must be unitized (broken-down into parts). • Units must be heuristic. • A unit of textual data is also called a concept. • First order concepts • Second order concepts • Textual units are not generally standardized.

4. Step 3: Developing Coding Categories • Coding categories are developed through an iterative process. • There are several types of coding processes: • Housekeeping coding • Research process coding • Analytic coding • Constant Comparative Method • Analytic Induction

5. Processes of Categorizing • Read all of your data completely in order to immerse yourself in them. • Identify your first unit of data. • Identify your second unit of data. • Make a basic judgment of similarity-difference between these two units. • Proceed with the similarity-judgment task for all your units of data. • Develop category labels and descriptions (memoing) for each of your categories. • Start over.

6. Step 4: Plugging Holes • Additional data are collected to clarify connections between units of data in a given category. • Additional data are collected when there are few textual units in a category that the researcher find important. • Additional data are collected when logic suggests that particular categories are missing.

7. Step 5: Checking • Negative case analysis is a process in which the researcher “tests” categories against new data – searching for units that are deviant or discrepant. • Member checks are conducted by reviewing the researcher’s categories with informants. • Triangulation is used when the researcher applies her coding categories to other types of data or when additional researchers derive coding categories from the same data set.

8. Step 6: Finding Exemplars • Not all of the data will be reported in the final qualitative research report, exemplars are chosen to represent those data. • Exemplars are examples in the data that best illustrate or “bring to life” the categories. • Exemplars should be chosen for their “thick description” (Geertz, 1973) to enable the transferability of the study.

9. Step 7: Integrating Coding Categories • The relationships between coding categories are mapped. • This is a meta-coding activity.

10. Models of Qualitative Data Analysis

11. The Developmental Research Sequence (DRS) • The DRS is used to understand semantic relationships and rules of a given speech community. • The study of semantic relationships is MOST often featured. • There are four activities involved in the DRS: • Domain Analysis • Taxonomic Analysis • Componential Analysis • Theme Analysis

12. Grounded-Theory Development (GTD) • GTD MOST often features the study of rules. • The goal of GTD is inductive theory construction. • There are four primary activities involved in GTD: • Open Coding • Axial Coding • Process Analysis • Selective Coding