- Coding: Researchers can identify and label key themes, ideas, or concepts in the data and assign codes to them. They can then use the codes to organize and analyze the data.
- Thematic analysis: Researchers can identify and analyze recurring themes in the data to understand how participants make sense of their experiences and construct meaning.
- Case study analysis: Researchers can conduct in-depth analyses of individuals, groups, organizations, or events to understand their experiences and contexts.
- Narrative analysis: Researchers can analyze stories or narratives told by participants to understand how they make sense of their experiences and how they construct their identities.
- Discourse analysis: Researchers can analyze the language and communication patterns used by participants to understand how they construct meaning and how they use language to assert their identities and positions.
- Grounded theory: Researchers can use a systematic process to generate a theory from the data. This process involves coding the data, identifying themes and patterns, and developing a theory that explains the relationships between the themes and patterns.
- Phenomenological analysis: Researchers can analyze the meaning and essence of participants' experiences to understand how they perceive and make sense of the world.
- Ethnographic analysis: Researchers can analyze the culture, social structure, and beliefs of a group to understand how they shape people's experiences and behaviors.
- Content analysis: Researchers can analyze texts, images, or other forms of media to understand how they are constructed and how they convey meaning.
- Framework analysis: Researchers can use a predetermined framework, such as a theory or model, to analyze the data and understand how it relates to the framework.
- Conceptual analysis: Researchers can analyze the concepts and categories used by participants to understand how they construct meaning.
- Comparative analysis: Researchers can compare the data from multiple cases or sources to identify similarities and differences and understand how they relate to each other.
- Descriptive analysis: Researchers can describe and summarize the data to understand its main characteristics and patterns.
- Exemplary analysis: Researchers can select a few particularly illustrative or representative cases to analyze in depth to understand their context and meaning.
- Phenomenographic analysis: Researchers can analyze how participants' experiences of a phenomenon vary and how they categorize and describe those experiences.
- Process analysis: Researchers can analyze the steps, stages, or sequences involved in a process to understand how it unfolds and what factors influence it.
- Time series analysis: Researchers can analyze data collected over time to understand how it changes and what factors influence those changes.
- Cross-case analysis: Researchers can analyze data from multiple cases to understand how they are similar or different and what factors contribute to those similarities or differences.
- Comparative-historical analysis: Researchers can compare data from different time periods or contexts to understand how they are similar or different and what factors contribute to those similarities or differences.
- Discursive analysis: Researchers can analyze the language and communication patterns used by participants to understand how they construct meaning and how they use language to assert their identities and positions.
- Historical analysis: Researchers can analyze data from the past to understand how it relates to the present and how it has changed over time.
- Ethnomethodological analysis is a qualitative research approach that examines how people make sense of and produce their everyday social worlds. It involves studying the ordinary practices and ways of knowing that people use to understand their social world and includes techniques such as participant observation and informal conversation.
- Interactional analysis: Researchers can analyze the interactions and communication patterns between participants to understand how they construct meaning and negotiate their relationships.
- Conversation analysis: Researchers can analyze the language and communication patterns used in naturalistic conversations to understand how participants construct meaning and negotiate their relationships.
- Autoethnography: Researchers can analyze their own experiences and identities in relation to a specific cultural or social group.
- Cultural analysis: Researchers can analyze the cultural values, beliefs, and practices of a group to understand how they shape people's experiences and behaviors.
- Sociolinguistic analysis: Researchers can analyze the language and communication patterns used by a group to understand how they construct their identities and relationships.
- Rhetorical analysis: Researchers can analyze the language and communication patterns used by participants to persuade or influence others.
- Hermeneutic analysis: Researchers can interpret the data in the context of the participants' experiences and meanings.
- Phenomenological reduction: Researchers can analyze the data by bracketing or suspending their own preconceptions and assumptions about the phenomenon being studied.
Neuman, W.L. (2008). Social research methods: Qualitative and quantitative approaches (6th ed.). Boston, MA: Pearson Education.
Creswell, J.W. (2013). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). Thousand Oaks, CA: Sage Publications.
Denzin, N.K. & Lincoln, Y.S. (Eds.) (2011). The Sage handbook of qualitative research (4th ed.). Thousand Oaks, CA: Sage Publications.
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