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Qualitative Analysis in NVivo
Introduction
Remember in thematic analysis (and other qualitative analysis approach), you need interview extract, codes, and themes. Codes is a function of the interview extract as themes is a function of codes. Therefore, they are all related. Often, you will need to go through your text several times to infer codes and themes. With the help of NVivo this task is made really simple!
With the growing large volume of qualitative data, the needs arise to deploy the use of application to analyze all forms of data that are not discrete and continuous. By supplying your survey response to NVivo you could identify codes, themes and results you may like to obtain.
Framework matrices can help us understand our data and handle massive numbers of interview data by breaking it down into more manageable portions.
Secondly, framework matrices are made up of a grid with columns for codes and rows for cases, such as the individuals we interviewed. Each grid cell symbolizes the point where a case and a topic cross; by entering text into the cell, we can produce a summary of the information pertinent to that case and theme.
What is coding
Remember in thematic analysis, you need interview extract, codes, and themes. Codes is a function of the interview extract as themes is a function of codes. Therefore, they are all related. Often, you will need to go through your text several times to infer codes and themes. With the help of NVivo this task is made really simple!
Well, coding is like assigning specific labels to some extract in the text. However, the data analyst is to decide what the labels are or should be and decide the text to extract, but generally, coding helps open up the data, which helps to generate an understanding of the data without having to read through every text in the data to extract meaning. However, NVivo offers auto coding methods and queries to assist us in creating codes based on the information in our files.
Coding queries by Overlapping and attribute
Using coding queries, we can test concepts, look for trends, and draw the dots between our project's themes, subjects, people, and locations.
Therefore, to create coding queries, we need to go to the top of the menu option and Click on Queries, then on coding as shown below in figure 1.
After clicking on coding, the windows below are displayed as shown in figure 2; So; therefore, label [1] is where the code has been created or can be created; label [2] is where we can select items, folders, files or attribute we want to query in the data and then label [3] is where the condition is selected based on what we want to get or see and label [4] is where we choose the code to select.
Finally, label [5] is where we can view our overlapping code or text extract to see the summary, reference and text resulting from the query. However, from figure 2, code strips are used to find the overlapping keyword in every query.
Coding queries by others
The specialized text search feature and the Query Wizard provide the same choices in a slightly different presentation. We can execute text searches from either one.
To list the terms that appear most frequently in our files, use word frequency queries. Using a word frequency search, we can search for a particular phrase in the file we want from the project, and potential themes can be considered.
As shown in the figure, word frequency queries are used to investigate a particular demographic's vocabulary in a given folder, extract or node, as shown below in figure 4.
Visualising our coding
In order to plot the histogram to represent Male and Female footballers, we have to select the chart option in the menu and select the case-by-attribute value; then, the histogram is shown, but the chart can be displayed in a 3-dimensional format.
This visualization can also be exported out of NVivo however, the sample image shown below can have more bars depending on the numbers of code and file classes contained, as shown in figure 5.
Charts, hierarchy charts, comparison and explore diagrams, cluster analysis diagrams, and sociograms are graphical representations of chosen data from projects. Maps are more dynamic and let us see our ideas differently.
The Explore diagram shows all the words or phrases connected to a given item or word, which enables us to investigate a connection or association in the word or extract, as shown in figure 6.
A cluster analysis diagram in NVivo is an exploratory tool that groups files, codes, or instances with similar terms, attribute values, or coding to help us find trends in our data.
It generates diagrams that use colour (to indicate "clusters") and location (similar items are near together and different things apart) to graphically depict the similarity or dissimilarity of the objects we are comparing.
These can be seen after we have generated or run the query of our word frequency, so the cluster diagram can be seen by selecting the bottom left edge in the NVivo interface, as shown in figure 7.
We utilize a word frequency inquiry to determine our study participants' topics. From the Explore tab, launch the search as shown in figure 8.
Choose the files to run the query on, the number of words to count, and whether or not we want to treat related terms as synonymous. The query can be seen as a word cloud once it has been executed.
A report comprises details taken from the project's underlying data. Depending on the "view" of the data we select, we may be able to include different fields in our report. For instance, the majority of the attributes related to codes, such as code name, description, or originator, are included in the Code view.
Text report: we may also base our report on the standards from a text report that is already part of our project; several basic text reports are available in NVivo, which we can use but can also create our own, but the report is only created based on the query we have run.
However, this report can be created by selecting share on the Nvivo menu bar, then selecting either a newly formatted text report or text report that can be customised and exported to any format needed; figure 8 below is the sample report.
The transparency of our study findings is further improved by using NVivo to organize and analyze our data. We used framework matrices and notes to show how our ideas can be developed and recorded our early prejudices and assumptions to show how they have been identified and challenged.
When coding, it is necessary to consider our findings after studying and coding a file then, run a report to check which codes have been used most frequently or display coding stripes to examine our code.
Finally, we can find illustrated quotations easily by constantly going back to the context in which our coded material was intended. The queries and visualizations that assisted us in reaching the primary purpose of our findings should be saved and reviewed or viewed from different angles.
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