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An Introduction to Qualitative Data

Analysis

Video Title: An Introduction to Qualitative Data Analysis

Originally Published: 2017

Publishing Company: SAGE Publications Ltd

City: London, United Kingdom

ISBN: 9781473992290

DOI: https://dx.doi.org/10.4135/9781473992290

This PDF has been generated from SAGE Research Methods.

https://dx.doi.org/10.4135/9781473992290

[An Introduction to Qualitative Data Analysis]

PROFESSOR ERIC JENSEN: My name is Eric Jensen, I'm an Sociology Professor at the University

of Warwick. [Dr. Eric Jensen, Sociology Professor]

DR. CHARLES LAURIE: And I'm Charles Laurie, Director of Research at Verisk Maplecroft. [Dr.

Charles Laurie, Director of Research]

PROFESSOR ERIC JENSEN: This video is about how to analyze qualitative data. So qualitative

data analysis is the process of identifying patterns in written information, audio recordings, video, or

images. There are no universally accepted rules for this process that define exactly, step by step,

what you must do. But you should be thorough and detailed in your approach.

PROFESSOR ERIC JENSEN [continued]: There are different fully valid pathways to arrive at a good

understanding of your data through qualitative analysis. [What is qualitative analysis?]

DR. CHARLES LAURIE: Qualitative research is open ended by nature and relies on your judgement

to find patterns through the haze of words in your audio recordings or transcripts. While such

judgements can be personal and subjective, techniques specified in this segment can help you

ensure that your analysis is systematic.

PROFESSOR ERIC JENSEN: Qualitative analysis is not about writing an opinion on a research topic

or selecting a couple of quotes that support an argument you already decided you wanted to make.

You must develop a clear analytical route from your data to specific patterns. And ultimately, to a

written report containing representative examples from your data that show these patterns.

PROFESSOR ERIC JENSEN [continued]: [Finding Qualitative Data]

DR. CHARLES LAURIE: Your first step in qualitative analysis is to take stock of the data and

contextual information available to you. Written qualitative data can be anything from interview

transcripts to field notes or a broad range of other written materials, including diaries and even

meeting notes. Whatever form your data take, your need to organize them

DR. CHARLES LAURIE [continued]: to make sense of what you have.

PROFESSOR ERIC JENSEN: When you think of bulleted of data, your initial decision might be

interview recordings and transcripts. However, you might be surprised at how much additional

information you can collect along the way as your research project develops. You can find yourself

with information such as diaries, photographs, and a range of personal, business, or government

documents.

PROFESSOR ERIC JENSEN [continued]: Such unplanned data is part of the open ended nature

of qualitative research. Just be sure to document how you gathered any new data sources that you

might draw upon in your analysis.

DR. CHARLES LAURIE: At this point, as you begin your positive data analysis by taking stock of

your information, its worth distinguishing between background information you use to provide context

and data that you systematically scrutinized through the data analysis process. Data are comprised

of pieces of information you have to find in your Methods section

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DR. CHARLES LAURIE [continued]: as the focus of your research. Your results will be based on

these data.

PROFESSOR ERIC JENSEN: By contrast, background information can help you understand the

data and provide context for that data. For example, miscellaneous historical information or notes

you come across won't necessarily be analyzed systematically. However, they still can play a role by

providing insights into the broader picture of how your participants' lives are constructed.

PROFESSOR ERIC JENSEN [continued]: [Context and Data]

DR. CHARLES LAURIE: Once you have separated out your data from background information, you're

ready to begin an analysis of these data.

PROFESSOR ERIC JENSEN: With a qualitative project, your analysis begins in the Methods section.

Here, you explain who you collected data from and why and what circumstances and over what period

of time. This context orients your analysis and establishes the boundaries of the kinds of knowledge

claims that you can make.

DR. CHARLES LAURIE: Your data only holds meaning when it can be situated within the context of

its collection. For example, if you conducted an interview with an elderly person in a care home, in

order to understand perceptions of aging, you would need to take account of the location in which the

interview was conducted. That is, within the walls of the home where the participant is cared for by

the staff.

DR. CHARLES LAURIE [continued]: If the participant reported that she felt well cared for by the

staff, was this answer influenced by the environment in which it was collected, such as the possible

presence of staff. Participants may have felt pressure to give certain answers or felt guilty about giving

negative feedback while in the setting. Or may have felt none of these things and given completely

frank interviews.

PROFESSOR ERIC JENSEN: Location is just the tip of the iceberg when it comes to the role of

context in qualitative research. Because gathering data for qualitative research relies so heavily on

the research or subjectivity, the analysis often needs to address the way in which the researcher may

have influenced the results. Indeed, there is an extensive academic literature

PROFESSOR ERIC JENSEN [continued]: on how the qualities of the researcher, herself or himself,

can influence the results that emerge. [Beginning Data Analysis]

DR. CHARLES LAURIE: Now that you have accounted for contextual influences affecting your data,

you can begin your focused analysis of the content of your data. There are many possible ways to do

this. We advocate a wider use approach we're calling pattern analysis. In this process, you take the

words and images and any other features you think are salient comprising

DR. CHARLES LAURIE [continued]: your data and categorize them using codes, which are specific

categories for the grouping of your data that apply across a number of individual quotations. The

word code can be a confusing piece of qualitative research jargon because code has many other

meanings. For example, in the context of computers.

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DR. CHARLES LAURIE [continued]: In social research, coding simply means making and applying

categories to your data. You can use your code to develop comparisons and connect your data to

relevant theoretical concepts you've located in your literature review. Taken together, these codes,

comparisons, and concepts help you build explanations that address your research

DR. CHARLES LAURIE [continued]: questions. Therefore, they will help you build your analysis from

data to codes to comparisons to concepts and finally, to explanations. [Coding the Data]

PROFESSOR ERIC JENSEN: It's worth going into more depth on the process of coding because

it's fundamental to qualitative analysis. After refreshing your memory by re-reading your field notes,

interview, or focus group notes, you begin reading transcripts and other written data, listening to the

audio, or viewing the video data. Your aim is to establish a firm grounding in your data

PROFESSOR ERIC JENSEN [continued]: by understanding what your participants are saying and

why before you start constructing explanations about what's going on.

DR. CHARLES LAURIE: You begin by setting up a series of initial code categories of the issues you

are expecting to see. This, again, highlights the value of beginning your analysis or at least a careful

reading of your data early on so your thinking can be well to developed by a stage.

PROFESSOR ERIC JENSEN: After coding your first transcript and adapting the codes as needed in

this first pass, you then move on to the next transcript and continue the process of applying codes

and tell your transcripts have all the coded. Once you've finished a complete first pass, you would

then start again, doing one pass after another until you're certain that you've captured as much depth

PROFESSOR ERIC JENSEN [continued]: possible for all your transcripts or until you run out of time.

DR. CHARLES LAURIE: Keep noting down the analytical thoughts that occur to you during the coding

process, however droll or incomplete the thoughts may seem. Are you finding interesting connections.

Have the accounts inspired you to do some additional readings. Are you seeing connections between

the data and theory you've been reading about.

PROFESSOR ERIC JENSEN: It's essential to record these thoughts as you go because they're often

fleeting and can be easily forgotten. Also, by recording these memos as they're called within your

positive data analysis software, they will all be in one place and you can electronically connect them

to the piece of data that sparked the thought within the software. You'll be grateful for the easy access

to your memos

PROFESSOR ERIC JENSEN [continued]: when you get to your writing up phase later on. [Theory,

Concepts, and Data Analysis]

DR. CHARLES LAURIE: During the coding process, think about how you can connect your findings

to theoretical concepts. Go back to concepts in your research question and literature review and look

for other related theoretical concepts that you could apply to see if they fit with your data. If existing

concepts don't help explain your data, then you may need to develop new or adjusted concepts

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DR. CHARLES LAURIE [continued]: to explain your findings.

PROFESSOR ERIC JENSEN: For instance, imagine the qualitative research as addressing a topic

relating to social class. She might start with the idea or concept that class identities are passed on

from one generation to the next because the upper class oppresses the poorer class. This is the

concept of oppression. If her data shows that the poorer class takes pride

PROFESSOR ERIC JENSEN [continued]: in its identity and values, then she can conclude the

concept of oppression is insufficient to explain the data that she has collected. In this case, a new

explanation might require using a different analytical concept, such as the idea of a working class

subculture. In this way, qualitative analysis must draw upon, modify, or create theoretical concepts

PROFESSOR ERIC JENSEN [continued]: that are useful in developing explanations that may be

applicable beyond the immediate context of the project.

DR. CHARLES LAURIE: One of the many advantages of coding is that the process allows you to

closely engage with the actual words and ideas of your participants. This means that as you code,

you'll be able to use data extracts to develop your emerging analysis.

PROFESSOR ERIC JENSEN: Never cherry pick your data extracts based on what fits your

preexisting assumptions about a topic. That's all too easy to do. But good quality of research faces

up to the uncertainties, contradictions, or unexpected patterns of the data, rather than pretending that

results are just simple and clear.

DR. CHARLES LAURIE: For instance, imagine a comparative analysis of men's and women's

attitudes about marriage based on semi-structured interviews. Perhaps the research expects that

men would display more commitment phobia while women will be more eager to tie the knot. But

the results of the analysis indicate that women and men who were interviewed were both equally

commitment phobic.

DR. CHARLES LAURIE [continued]: Rather than trying to make the data fit the theory by executing

interviews with commitment phobic women from the analysis, the best strategy here would be to seek

explanations from the unexpected findings. Also, the researcher might seek to clarify the analysis by

conducting follow up interviews or by reading up on the literature about gender roles to find existing

explanations that the study might support

DR. CHARLES LAURIE [continued]: or indeed, challenge. [Computer Assisted Qualitative Data

Analysis Software (CAQDAS)

PROFESSOR ERIC JENSEN: There are several qualitative analysis software packages sometimes

referred to as Computer Assisted Qualitative Data Analysis Software, or CAQDAS for short. These

products can help you get the most out of your raw qualitative data. They kind of operate like Microsoft

Word does for writing essays.

DR. CHARLES LAURIE: Some qualitative researchers have criticized such software for alienating

researchers from their data and sometimes for causing an over emphasis on coding to the exclusion

of other aspects of qualitative analysis. However, the predominant opinion in methodological literature

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indicates that minor limitations stemming

DR. CHARLES LAURIE [continued]: from qualitative analysis software are more than adequate by

increases in productivity, reliability, consistency, and transparency.

PROFESSOR ERIC JENSEN: Once you've completed your coding passes and ended up with a set

of patterns of you've identified within your data, you will have combined or adjusted codes along the

way and created notes that document any initial ideas you had.

DR. CHARLES LAURIE: You may also have made comparisons between perspectives within each

sample or indeed, between samples, to get a clearer sense of the range of views emerging from

your data. In addition, you should have started making connections to key ideas from your literature

review, especially theoretical concepts that can help you account for your data.

DR. CHARLES LAURIE [continued]: These are the first crucial steps in developing a systematic

analysis of your data. However, there are still several more steps to take in your qualitative analysis

to ensure that it's as robust and insightful as possible. [Writing Up the Analysis]

PROFESSOR ERIC JENSEN: While qualitative data analysis software is an excellent tool to help

you manage and make sense of your data, your analysis extends into the writing up process. Moving

your analysis code by code into your research report document as an essential step, which can also

result in new insights. Laying out your ideas on the page, thinking them through as you write each

paragraph,

PROFESSOR ERIC JENSEN [continued]: and then repeatedly reviewing and rethinking what you've

written to deepen your analysis and sharpen your claims is the key to developing a high quality

qualitative data analysis report. [Conclusion: Ensuring Quality in Qualitative Data Analysis]

DR. CHARLES LAURIE: Let's now think about quality in your qualitative analysis. Many factors can

intervene to undermine the quality of your analysis. First, let's consider your role as the decision

maker about how your data will be collected and analyzed. You're likely to have some ideas about

what you expect to find from your research before you start your project.

DR. CHARLES LAURIE [continued]: You need to practice letting go of those ideas and be completely

open to where your data will take you. While you work be able to completely achieve this goal, striving

to keep an open mind is valuable in itself.

PROFESSOR ERIC JENSEN: You can help ensure the quality of your analysis by employing a few

strategies. First, make sure that you transcribe and read your positive data during the data collection

process to put you in a strong position to remember relevant contextual details that you add to your

field notes. Doing this can also help you by creating a feedback loop so

PROFESSOR ERIC JENSEN [continued]: that your ongoing analysis feeds back into your qualitative

data collection in the form of revised or new interview or focus group questions. Also, make sure you

read up on methodology in your particular sub-field. For example, if you're using blogs as your data,

delve into articles or books on methodology and web-based research to ensure you're fulfilling the

quality

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PROFESSOR ERIC JENSEN [continued]: expectations in this domain. Don't try to tie up every loose

end or smooth over every rough patch in your qualitative analysis. With qualitative analysis, you're

allowing for diversity in people's perspectives and experiences. Also, you don't have to account for

every scrap of data that you've collected. At some point, you'll have to make

PROFESSOR ERIC JENSEN [continued]: a judgment about which aspects of your findings are most

relevant to addressing your research question. And also, don't try to do everything. Don't be afraid to

make the judgement that something is beyond the scope of your analysis. Just as you must narrow

the scope of your research project early in your project in order to keep it nice and focused, you also

need to keep the scope tightly focused

PROFESSOR ERIC JENSEN [continued]: within your qualitative analysis.

DR. CHARLES LAURIE: There is a growing body of methodological literature advocating quality

assurance techniques to help insure quality in your qualitative analysis. Each qualitative research is

different and every instance of generating qualitative data will develop in different ways due to the

dynamics between the researcher, the participants, the research

DR. CHARLES LAURIE [continued]: questions, and the situation in which the data is gathered.

Therefore, instead of validity and reliability, techniques such as thick description, transparency, and

procedural clarity, deviant case analysis, and reflexivity will raise the quality of your analysis.

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An Introduction to Qualitative Data Analysis