Atlas Ti Code Category Versus Family Versus Group

ATLAS.ti 9 Windows - User Manual

Building a Code System

A well-structured lawmaking list is important for farther analysis, where you wait for relationships and patterns in the data, with the goal of integrating all results to tell a coherent story. If, equally in a survey, you just have questions with the answer categories "yes" and "no" in your questionnaire, your data will only consist of nominal variables. This ways that the analysis is limited and does not go beyond the descriptive level. This is like a code listing that consists of a ready of codes whose analysis level remains indefinite.

See also: Creating a coding scheme with ATLAS.ti.

Benefits of a well-structured lawmaking list

• it creates order
• information technology brings conceptual clarity for yourself and others
• information technology provides a prompt to code additional aspects as you go on to code
• it volition assist y'all in identifying patterns

Characteristics of a well-structured code list

• Each code is distinct, its pregnant is different from the meaning of whatever other code.
• The meaning of each lawmaking is described in the lawmaking comment.
• Each category can exist clearly distinguished from other categories.
• All sub codes that belong to a category are similar as they represent the aforementioned kind of thing. Nonetheless, each sub code within a category is distinct.
• Each code appears only one time in the lawmaking organization.
• The lawmaking organisation is a-theoretical. This means the code organization itself does not represent a model nor a theory. The codes merely describe the information, and so that the data can easily be accessed through them.
• The code system should be logical, and then you lot can notice what you are looking for.
• The code system contains betwixt 10 and 25 peak-level categories.
• The lawmaking organisation has no more than than two to 3 levels. Thus, it consists of categories and sub codes, and possible a dimension like positive / negative, or a time indicator similar earlier / during / afterward. If dimensions apply to many codes in the lawmaking system, it is meliorate to create carve up codes and double-code the data with the content code plus the dimension.

Below is a bibliography of the articles and authors on which these recommendations are based.

How to Begin Edifice a Code Arrangement

The aim of building a code system is that y'all can access your information through the codes and that you can brand full use of the analysis tools. For example, knowing you tin can cross-tabulate codes using the code co-occurrence tabular array helps to empathise why it is important to lawmaking in an overlappin

Yous start by creating codes to catch ideas, the listing of lawmaking grows. You so begin to sort and order codes into categories and sub codes making use of the merge and split functions. It is recommended to develop categories that comprise simply one level of sub codes (two if necessary). This allows yous to flexibly combine different aspects when querying the data, and to avoid unnecessary long code lists and code labels.

You will observe that you have different types and levels of codes:

• Structural codes that code speaker units in focus groups
• Aspect codes that code sociodemographic attributes of speakers or persons within a document
• Codes that indicate a category and codes that are sub codes of a category, and so on.

Every bit in that location is merely one entity for all of these different things - the code - you can indicate unlike types and levels using the lawmaking label. The table below proposes a syntax that you can use as guideline:

Syntax for Different Types and Levels of Codes

What	Syntax for Code Label	Case
Initial concept	Lower case	personal growth
Category	UPPER CASE, colored	Issue
Sub code	Lower example, same as category color	Effects pos: personal growth
Concept that does not fit whatever category	asterisk (*) label in lower case	*scientific testify
Dimension	Lower case + special character, coloured	/time: during
Sociodemographics	prefixed with #	#gender: female
speaker units	prefixed with @	@Tom

---

Instance

# gender: female

# gender: male

@Tom

@Maria

@Clara

/time: earlier

/time: during

/fourth dimension: after

*single code 1

*single lawmaking two

*unmarried code 3

CATEGORY A

category A: sub 1

category A: sub 2

category A: sub iii

CATEGORY B

category B: sub 1

category B: sub 2

category B: sub 3

You see that the prefixes dissever your code system into different sections. This helps you to keep organized and to quickly find what you are looking for. It likewise allows you to flexibly combine the codes of the dissimilar categories or categories with speakers, attributes and dimensions when querying the data.

Beneath yous see a screenshot showing a structured code list in ATLAS.ti:

The first ii codes are abstract codes (= 0 frequency) that are used every bit modifier codes in networks. By the loftier density y'all tin see that they have lot of links to other codes. Combatants and non-combatants are actually document groups in the analysis projection. As yous however cannot link groups to --> codes, these codes accept been introduced to show the deviation between the two respondent groups in networks.

If you desire to read more most the project and how this code list was developed, yous can read the following newspaper: CAQDAS and Grounded Theory Analysis.

If you have interview data, instead of attribute codes, yous use document groups to sort documents by attributes like gender, age, family status and the like.
tip
Organize your code structure based on conceptual similarities, not observed or theoretical associations, nor co-ordinate to how you think your will want to write the consequence chapters.

Apply a separate code for each element of what the text is well-nigh, i.e., each lawmaking should encompass 1 concept only. If there are multiple aspects, the passage tin can be coded with multiple codes.

Don't worry if non all of your codes tin can exist sorted into a category. Some codes will remain single codes. In order not to "loose" them in the categories, employ a special prefix, so they bear witness upward in their own department in the code system.

The Office of Code Groups in Edifice a Code System

Users are ofttimes tempted to use code groups as higher society categories. This defeats the purpose somehow. Code groups are filters and codes can be assigned to multiple lawmaking groups. A code of one category tin can however only belong to one and not to multiple categories. This is why code groups practice non serve well as college order codes. If you want to build categories and sub codes, the recommendation is using the in a higher place suggested syntax instead. Betoken a category past using upper-case letter letters.

If you have a lot of low frequency code that you lot desire or need to merge, so code groups are a good fashion to collect them. After you accept added all low level codes that belong to the aforementioned theme / topic / idea, you tin set this code grouping as filter. This makes it easier to merge the codes. You lot can then add prefixes, and the category code in majuscule messages.

Once you accept adult categories with sub codes, you can create a code grouping for each category for the purpose of using it every bit filter. Code groups volition allow you to filter past categories, and for farther assay, y'all can employ the code groups to analyse on the category level rather than the sub lawmaking level. See Friese, S. (2019). Qualitative Data Analysis with ATLAS.ti. London: SAGE Publications.

Moving on

Once the data is coded, you lot have a practiced overview of your cloth and can draw it. You tin can then take the assay a footstep further by querying the data. The tools that tin can be used include the code co-occurrence tabular array, the code document table, the query tool, and the networks.

The goal is to delve deeper into the data and find relationships and patterns. Writing memos is very important at this phase as much of the assay does not but happen because y'all apply a tool. The insights come when reading the information resulting from a query, and when writing summaries and interpretations.

Literature

The recommendations in this section are based on the post-obit authors:

Bazeley, Pat (2013). Qualitative Information Analysis: Applied Strategies. London: SAGE Publications. Bernard, Russel H. and Ryan, Gery W. (2010). Analysing Qualitative Data: Systematic Approaches. London: SAGE Publications. Charmaz, Kathy (2006/2014). Amalgam Grounded Theory: A Practical Guide Through Qualitative Assay. London: SAGE Publications. Corbin, Juliet and Strauss, Anselm (2008/2015). Basics of Qualitative Inquiry: Techniques and Procedures for Developing Grounded Theory (3rd and 4th ed.). Thousand Oaks, CA: SAGE Publications.

Freeman, Melissa (2017). Modes of Thinking for Qualitative Data Analysis. NY: Routledge.

Gibbs, 1000. (2008). Analysing Qualitative Data. London: SAGE. Guest, Yard., MacQueen, One thousand.M., and Namey, E.E. (2012). Applied Thematic Analysis. Los Angeles: SAGE Publications.

Hammersley G, Atkinson P (2007) Ethnography: Principles in Practise. Third edition. London: Routledge.

Johnston, 50. (2006). Software and method: Reflections on didactics and using QSR NVivo in doctoral inquiry. International Periodical of Social Research Methodology, ix(5), 379–391.

Miles, Matthew B., Huberman, Michael, Saldaña, Jhonny (2014). Qualitative Data Assay (3rd ed.) Chiliad Oaks, CA: SAGE Publications.

Morse, J.Grand. and Richards, L. (2002, 2013). Readme First for a User's Guide to Qualitative Methods (third ed). Thousand Oaks, CA: SAGE Publications.

Richards, Lyn (2009, 2021, 4ed). Handling qualitative data: A practical guide. London: SAGE Publications.

Saldaña, Jonny (2021). The Coding Manual for Qualitative Researchers. London: SAGE Publications. Spradley, James P. (2016). The Ethnographic Interview. Waveland Press. Strauss, A. (1987). Qualitative analysis for social scientists. Cambridge, Great britain: Cambridge University Press.

Weston, C., Gandell, T., Beauchamp, J., Beauchamp, C., McApline, L. and Wiseman, C. (2001). Analyzing Interview Information: The Evolution and Development of a Coding System, Qualitative Sociology 24(3): 381-400.

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