D: Tracy (2013): Ch 9 Data analysis basics, a pragmatic iterative approach

Question 1

Iterative analysis

Answer 1

Alternates between emic and etic use of existing models, explanations and theories

Question 2

Iterative analysis

Answer 2

Alternations between emic and etic use of existing models, explanation and theories
Rather than grounding the meaning solely in the emergent data, it encourages reflection upon the active interests, current literature and various theories
A reflective process in which the researcher visits and revisits the data, connects them to emerging insights and progressively refines focus and understandings

Question 3

Steps for the iterative process

Answer 3

Organize and prepare your data
Analysis logistics
Data immersion and primary-cycle coding
Focusing the analysis and creating a codebook
Secondary-cycle cosign
Synthesizing and making meaning from codes

Question 4

Steps for the iterative process: organize and prepare your data

Answer 4

Prepping all the raw materials: field notes, interview transcripts, key documents, links to electronic files and websites
You can organize chronologically, beneficial as your show the trajectory of your analysis
You can organize using type of data collection
You can organize by source or demographic attributes

Question 5

Steps for the iterative process: analysis logistics

Answer 5

Coding: labelling and systematizing the data
Manual approach: gaiters copies of all data and mark with ens, pencils and highlighters
Computer aided approach: color coding, use excel, atlas.ti, word, google docs

Question 6

Steps for the iterative process: data immersion and primary-cycle coding

Answer 6

Primary cycle/first-level codes: focuses on what is present in the data, descriptive, showing the basic actives and processes in the data
In-vivo codes: use the language and terms of the participants themselves and can be helpful in identifying personal use of vocabulary
Constant comparative method: comparing the data applicable to each code and then modifying code definitions to fit new data

Question 7

Steps for the iterative process: focusing the analysis and creating a codebook

Answer 7

Codebook: a data display that lists key codes, definitions and examples that are going to be used in your analysis
Code books are like ‘legends’ for your data, helping you meet the challenge of getting your head around pages of transcripts, highlights and scrawling

Question 8

Steps for the iterative process: secondary-cycle coding

Answer 8

Critical examining the codes already identified in the primary cycle and organize, synthesis and categorize them into interpretive concepts

Question 9

Steps for the iterative process: synthesizing and making meaning from codes

Answer 9

Analytics memos: sites of conversation with ourselves about our data and a place to dump our brain, a longer version of the field note’s analytic asides and are usually focused on the meaning of codes and on the connections among them

Question 10

Analytics memos

Answer 10

Define the code as carefully as possible
Explicate its properties
Provide examples of real data that illustrate the code
Specify conditions under which it arises, is maintained and changes
Describes its consequences
Show how it relate to other codes
Develops hypotheses about the code