QUALITATIVE RESEARCH METHODS

DATA ANALYSIS/CODING

GROUNDED THEORY

I. GROUNDED THEORY

• A. A qualitative approach to theory-building developed by sociologists Barney Glaser & Anselm Strauss. – 1. Works to establish theory from data– 2. Opposed to more typical scientific approaches

where researcher applies a theoretical framework or model to the studied phenomenon

– 3. Instead, propositions arise from data, untainted by previous theory

– 4. Basically, it is a systematic generation of theory using both inductive & deductive thinking

– 5. Not descriptive so much as generative of concepts

Grounded Theory, con’t.

– 6. Glaser argues it is a general method, applicable to any type of research (quantitative or qualitative)

• B. Goals/Purposes of Grounded Theory (GT)– 1.To formulate hypotheses based on conceptual

ideas • a. Generated by constantly comparing

conceptualized data on different levels of abstraction

• b. Contain deductive steps that permit others to test the hypotheses

Grounded Theory, con’t.

• 2. To discover the participants’ main concern(s)– a. Keep asking "What’s going on?“ "What is the main

problem of the participants?” & “How are they trying to solve it?“

– b. These questions answered by the core variable, its subcores & properties, as go through data

• 3. Does not aim for "truth" but to conceptualize what's going on by using empirical data

• 4. Results of GT are not to report statistically significant probabilities

Grounded Theory, con’t.

• 6. Instead, develop a set of probability statements about the relationship between concepts, or an integrated set of conceptual hypotheses developed from empirical data (Glaser 1998)

• 7. Judge validity by fit, relevance, workability, & modifiability– a. Fit is how closely concepts fit with the incidents they are

representing– b. Relevance deals with the real concerns of participants –not

only of academic interest– c. Has workability when explains how the problem is being

solved by participants– d. Is modifiable when new relevant data is compared to existing

data

Grounded Theory, con’t.

• C. Four stages of analysis (from Wikipedia):– 1. Codes--Identifying anchors (words, themes, other

patterns) that allow key aspects of the data to be gathered

– 2. Concepts--Collections of codes of similar content that allows the data to be grouped

– 3. Categories--Broad groups of similar concepts used to generate a theory

– 4. Theory--Collection of explanations about the subject of the research

Grounded Theory, con’t.

• D. Coding– 1. The researcher observes, holds conversations

(informal interviews) & more structured interviews– 2. After each event, write up field notes– 3. Use a comparative process to discover patterns or

themes in the data– 4. The key points are marked with a series of possible

codes, which are extracted from the text (often initially listed in the margins)

– 5. The codes are grouped into similar concepts in order to make them more workable

Grounded Theory, con’t.

• 6. From these concepts, categories are formed, which are the basis for the creation of a theory (also called a reverse engineered hypothesis)

• 7. As one codes, theoretical propositions should emerge (the “theory implicit in the data”) – a. A difference between “emergence” & “forcing”

(Glaser argues this occurs with more traditional hypothesis testing)

– b. Since both method & theory are emergent, there is little literature review in the traditional sense

Grounded Theory, con’t.

• E. Key ideas– 1. The core variable

• a. Explains most of the participants’ main concern with as much variation as possible

• b. It is parsimonious yet complete• c. It theoretically accounts for most of the variation

in change over time, context, & behavior in the studied area

• d. As Glaser (1998) said: "GT is multivariate. It happens sequentially, subsequently, simultaneously, serendipitously, & scheduled"

Grounded Theory, con’t.

• 2. All is data/Source data– a. Look at everything that comes one’s way in a

certain area – b. Not just interviews or observations, but also

anything that generates concepts for the emerging theory

– c. Can come from informal interviews, lectures, seminars, expert group meetings, newspaper articles, Internet mail lists, conversations with friends, one’s own knowledge, TV shows, etc.

– d. Write up using field notes

Grounded Theory, con’t.

• Data that provides the material from which codes are extracted is often largely based on observer notes, logs, diaries, etc. Additional data may also be found in items such as published and unpublished documents, papers, books, public records, letters, photographs, videos and assorted artifacts. The problem with data is that the more you have the more effort is required to analyze, and with time increasing sharply with the amount of data. Yet more data leads to better categories, theories and conclusions.

•  

• What is 'enough' data is subject to debate and may well be constrained by the time and resource the researcher has available. Deciding when and where to collect data can be a critical decision. A deep analysis at one point may miss others, whilst a broad brush may miss critical minutiae. Several deep dives can be a useful method.

Grounded Theory, con’t.

• 3. Theoretical sampling

•  Selection of data & cases for exploration can be based on one or more of three purposes: 

• to extend the emerging theory

• to replicate previous cases to test the emerging theory

• to extend the emerging theory by choosing a case that is a polar opposite

• The types of data selected in theoretical sampling often needs to be varied and is based on what is called 'slices of data' -- samples of many different kinds and sources rather than a focus on one area to the exclusion of many others.  

Grounded Theory, con’t.

• 4. Open Coding•  Coding starts with open coding, in which codes are identified

without any restrictions or purpose other than to discover nuggets of meaning. The main secret of open coding is a mental openness that allows for the discovery of the unexpected along with a curiosity that does not allow for final closure, even after texts have been read and codes identified from it. Coding is thus a very questioning activity. Open coding is particularly about labeling and categorizing of phenomena. This must be a careful activity as names come with many connotations.

Grounded Theory, con’t.

• The constant comparative method may be used by constantly comparing each piece of data with codes and notes already identified. Comparison helps identify distinct characteristics and ordinal position on any relevant scale.

• It is a trap to worry about the 'real meaning' of words, as this is a form of closure; open coding is about opening up lines of inquiry. Theoretical saturation is achieved when no further new codes or categories are being identified. Further analysis then only goes to test and support the identified theory.

•  Coding can be quite a tedious activity but it requires expertise. The quality of categories and theories depends on the quality of the coding. Employing others to help coding can very much speed the activity, but they do need to know what they are doing.

Grounded Theory, con’t.

• 5. Memoing•  Memos are theoretical notes that occur to the researcher as they

are coding and may at some time lead to the discovery of categories and may cause the researcher to go back to the data to explore more. Memos may identify concepts, half-formed ideas, action notes and other thinking that is a first step towards making cohesive sense from the data.

•  Ideas and meaning can be identified at any time, including when the work is not formally under way. When the mind is saturated with data, it can come up with ideas at the most inopportune moments. The researcher thus always carries note-taking equipment everywhere

• 5. Sorting•  Memos, categories and codes may be sorted at any time, looking

for relationships between them and priorities of the people involved when they need to make choices. This is also called data ordering. Priorities often emerge, much like other information, in an unstructured way as the subconscious realizes patterns after a long wading through the

• data. Items may, for example, be written on post-it notes or cards and moved around to form clusters or 'clouds' that can turn into categories or allow new relationships to be found. 'Category folders' may also be kept, containing clippings and codes on items that support a single category.

• Categories

•  Critical aspect of coding is the identification and naming of categories, such as 'greeting people' or 'vehicle breakdown,' Codes that lead to discovery of a 'greeting' category might come from observation of encounters with other people in which particular rituals and significance is identified. Categories can also include sub-categories, such as shaking hands' or 'removing the wheel.' Categories can include such as:

• Contextual conditions (eg. 'raining')

• Properties (eg. 'wet')

• Interactions (eg. 'approached by beggar')

• Strategies and tactics (eg. 'ignore them')

• Actions (eg. 'not looking')

• Consequences of actions (eg. 'receiving insults')

• Naming of categories is important as this gives a handle by which the category can thought about and discussed. Names come with previous meanings, so their choice is very important. For example, 'rain', 'raining' and 'precipitation' have a different impact on thoughts. Additional words may create a more precise phrase, such as 'heavy rain' or 'sudden showers.'

• Core category• The core category in a coding exercise is the central code or principle round which

other codes cluster. There is often one core category, although there can be more. For example a study of commuters might conclude the core category is 'going to work' and a study of teenagers could settle on 'growing up'.

• A core category should:• Be central, with many relationships to other categories. • Be easy to relate to other codes and categories. • Appear frequently in the data, denoting its importance. • Supports theories that already appear and which might be proposed. • Moves ideas forward as links and more meaning is uncovered. • The core category gives central meaning to the conclusions of the research and is

often the 'holy grail' that the researcher is seeking. It is the main theme of the situation and may represent a central problem or issue for the people involved. Once the core category is identified, then other related categories can be linked to it, leading to an integrated and coherent explanation of the subject of research.

• Axial Coding (Strauss)• Axial coding occurs where there is a strong focus on discovering codes around a

single category, for example looking for interactions, strategies and so on that relate to the category. For example in a category of 'greeting', there may be a search for encounters with others, talk about previous encounters and emotional impacts from meeting others.

•  Axial coding can also be used to develop categories, seeking relationships that will expose a category. Where open coding is about identification and naming, axial coding is about links and relationships. Strauss and Corbin (1990) identify a Paradigm Model by which coding looks for:

•   Causal conditions • Contextual factors • Actions and interactions taken in response to the phenomenon • Intervening conditions that assist or hinder actions and interactions • Consequences of actions and interactions

• Selective Coding

• Selective coding is even more focused as it works around the core category, looking specifically for links to it and how it may or may not be the heart of the matter. This particularly helps with integration of categories.

• Triangulation

•   When theory is being developed, 'triangulation' is finding a third element outside of the cause and effect items to corroborate apparent relationships. Where possible, quantitative data may be sought to triangulate qualitative findings.

• Discovering themes