Pain

• Data management

○ Use computer to organize data

○ "Fat data" collection more data

○ CAQDAS - computer software to organize data.

○ Code & retrieve programs - assist in organizing & grouping data

• Data collection should be completed before analysis begins

• Researcher needs to identify the process used & make meaning out of massive amounts of data.

• Data Reduction - selecting, focusing, abstracting & transforming the data

○ Data is organized into meaningful clusters of data by grouping related data.

• Themes - clusters of groups of data or occur frequently in the text.

○ It is structured meaning units of data & categorized via subthemes

• Thematic analysis - process of recognizing & recovering the emergent themes.

○ Free act of seeing meaning

• Codes - tags that assigned the themes during analysis.

○ Progressive marking and redefining of the collected data.

○ It allows researchers to transform the unstructured and messy data to ideas about what is going on in the data.

○ Major codes may exist along w. subcodes.

• Data display - organized info that permits conclusion action

○ Form of figures or graphs

○ Rich description & give meaning to experiences

○ Descriptive phenomenology - focus on the description of the lived experiences

○ Grounded theory study - focus on careful description of how the narrative give rise to the analysis, results in theory but development.

• Conclusion drawing - description of the RS between the themes

○ It starts at the beginning of data collection

• Verification - questioning own conclusion & checking w. past participants

○ Occurs as the data are collected

○ Constant comparative method: new data are compared as they emerge w. data previously analyzed.

○ Member checking - going back & checking w. the participants again

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