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β€’ Data management
β—‹ Use computer to organize data
β—‹ “Fat data” collection more data
β—‹ CAQDAS – computer software to organize data.
β—‹ Code & retrieve programs – assist in organizing & grouping data
β€’ Data collection should be completed before analysis begins
β€’ Researcher needs to identify the process used & make meaning out of massive amounts of data.
β€’ Data Reduction – selecting, focusing, abstracting & transforming the data
β—‹ Data is organized into meaningful clusters of data by grouping related data.
β€’ Themes – clusters of groups of data or occur frequently in the text.
β—‹ It is structured meaning units of data & categorized via subthemes
β€’ Thematic analysis – process of recognizing & recovering the emergent themes.
β—‹ Free act of seeing meaning
β€’ Codes – tags that assigned the themes during analysis.
β—‹ Progressive marking and redefining of the collected data.
β—‹ It allows researchers to transform the unstructured and messy data to ideas about what is going on in the data.
β—‹ Major codes may exist along w. subcodes.
β€’ Data display – organized info that permits conclusion action
β—‹ Form of figures or graphs
β—‹ Rich description & give meaning to experiences
β—‹ Descriptive phenomenology – focus on the description of the lived experiences
β—‹ Grounded theory study – focus on careful description of how the narrative give rise to the analysis, results in theory but development.
β€’ Conclusion drawing – description of the RS between the themes
β—‹ It starts at the beginning of data collection
β€’ Verification – questioning own conclusion & checking w. past participants
β—‹ Occurs as the data are collected
β—‹ Constant comparative method: new data are compared as they emerge w. data previously analyzed.
β—‹ Member checking – going back & checking w. the participants again

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Data Management And Major Codes. (April 3, 2021). Retrieved from