160 likes | 369 Views
Analysis of Qualitative Data. Planning Research Chapter 9. Analysis requirements. It requires that you make your own Interpretation and Highlighting patterns Grounded in the data in a way that can be recognized and understodd by readers of your research. Influence on Analysis.
E N D
Analysis of Qualitative Data Planning Research Chapter 9
Analysis requirements • It requires that you make your own • Interpretation and • Highlighting patterns • Grounded in the data in a way that can be recognized and understodd by readers of your research
Influence on Analysis • The analysis of your data will largely be influenced by • your theoretical perspective • Your research strategy • Your understanding about what might be relevant and improtant in answering your research question
1. Deductive Approach • The theory-driven approach helps you: • To describe and explain the patterns of relationships and interactions better, because you group the data according to codes • To bring to the surface themes that might not emerge from the inductive mode of analysis
Coding Schema • Highlighting the elements in the theory as codes to interoretation • A matrix of codes can be constructed • Exampel Boston Matrix
2. Inductive Approach • Try to have a relatively open mind towards the topic • Prevent yourself from being over-structured by ane preconceptions • Improve the quality and depth • Increase the validity and reliability • Use the following stage model:
Stage Model for Inductive Approach • Familiarization with the data • Coding, conceptualization and ordering • Open coding • Axial coding • Selective coding • Enfolding litterature
Stage 1. Familiarization • Interviews: • Listen to interviews several times • Take notes about possible interpretations • Identify emerging patterns • Other qualitative data • Re-read materials • Review organizational documents and published reports
Stage 2: Coding • Involves the generation of concepts through the process of coding • ”operations in which data are broken down, conceptualized, and put back together in new ways”
Open Coding • This is the initial stage of data analysis • Describing the overall features of the phenomenon • Data are broken down by asking simple questions like: • What, • where, • when, • how and • how much
Axial Coding • Is the next stage after open coding • Puts data back in new ways • By making explicit connections between categories • You need to create a system of coding to be able to identify causal relationships
Selective coding • Involve both open and axial coding • Forming a theoretical framework • (Often called a grounded theory) • The codes and categories are explored further by revisiting the data
Enfolding Literature • The data analysis yilds a number og themes, that can be compare to existing literature • Asking what these themes are similar to, what they contradict and why