Qualitative Methods for Research with MaxQDA -BriefExplanation · Qualitative Methods for Research with MaxQDA-BriefExplanation ... Qualitative Methods for Research with MaxQDA

Introduction Good Research Design Collecting Coding Tools Displays Reporting

Qualitative Methods for Research with MaxQDA- Brief Explanation

Vicenc [email protected]

May 30, 2016

Vicenc Fernandez

Qualitative Methods for Research with MaxQDA - Brief Explanation


Outline

Introduction

Good Research

Design of the Research

Collecting Data

Coding Data

Analysis Tools

Data Displays

Reporting the Research

Bibliography

Vicenc Fernandez



Introduction

Good Research


Collecting Data

Coding Data

Analysis Tools

Data Displays


Bibliography

Vicenc Fernandez



Kinds of paradigms

Approaches or paradigms of social research can be identified fromthe following three questions (Guba, 1991):

I Q1: How do we conceive the nature of both knowledge andreality? 1 or 2 realities.

I Q2: How do we conceive the nature of relationships betweenthe researcher and the knowledge? Independent or not.

I Q3: What is the way do the researcher develop or constructknowledge? To build from the experience or to testhypothesis.

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Understanding The Quantitative/ Qualitative Divide

Quantitative and qualitative research traditions represent afundamental debate in the production of knowledge.

The terms quantitative and qualitative, particularly in relation tomethodology, however, can be confusing, divisive and limiting.

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The Qualitative Tradition

The qualitative tradition critiques quantitative assumptions andpremises inductive logic, subjectivity, multiple truths, the politicalnature of research, and the value of depth over quantity.

Qualitative research strategies for achieving credibility includethoroughness, i.e. saturation, crystallization, prolongedengagement, persistent observation, broad representation and peerreview, and confirmation, i.e. triangulation, member checking, andfull explication of method.

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Traditions

I Ethnography

I Phenomenology (dialogic process)

I Ethnomethodology

I Feminist Approaches

I Symbolic interactionism

I Cognitive anthropology

I Holistic ethnography

I Ecological psychology

I Grounded theory.

To see more taxonomies: Tesch (1990), Jacob (1987), Sandoval(1996), & Taylor and Bogdan (1992 ).

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Mixed Methodology

’Mixed’ studies traverse traditional divides and can help youcapitalize on the best of both traditions while overcoming theirshortcomings.

’Mixed’ approaches can be premised in the quantitative traditionwith acceptance of qualitative data; the qualitative tradition withacceptance of quantitative data; or be driven by the questionsthemselves.

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Introduction

Good Research


Collecting Data

Coding Data

Analysis Tools

Data Displays


Bibliography

Vicenc Fernandez



General ConsiderationsCriteria for judging the quality

I 1. Objectivity

I 2. Construct validity

I 3. Internal validity

I 4. External validity

I 5. Reliability

I 6. Pragmatic validity

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General ConsiderationsMaking inferences

Statistical generalization

I First level

I To generalize the results of a sample to a population.

Analytic generalization

I Second level

I To generalize the results of a research to a theory and therival theory..

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General ConsiderationsMaking inferences

Industrial Engineering and Management Research Group [email protected]

Making inferences

!  Statistical generalization !  First level !  To generalize the results of a sample to a population

!  Analytic generalization !  Second level !  To generalize the results of a research to a theory and the rival theory.

THEORY Policy implication

RIVAL THEORY Rival policy implication

SURVEY Population

CASE STUDY findings

EXPERIMENTS findings

SAMPLE SUBJECTS

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COSMOS Corporation

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General ConsiderationsComputer software

Uses of Computer Software (Miles & Huberman, 1994):

I (1) Making notes in the field, (2) Writing up or transcribingfield notes, (3) Editing them, (4) Coding them, (5) Storagethem, (6) Search and retrieval them, (7) Data ’linking’ them,(8) Memoing, (9) Content analysis, (10) Data display, (11)Conclusion drawing and verification, (12) Theory building,(13) Graphic mapping, and (14) Preparing interim and finalreports.

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General ConsiderationsComputer software

The computer does not analyze, the researcher analyzes.Advise

I We cannot answer the question: What software is the best?

I Select software comfortable for you.

I To learn how a software works, you need to use it on real tasks

I Researchers need time to learn and set-up this software

I No single program can do everything well.

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MaxQDAGeneral information

MAXQDA is a professional software for qualitative and mixedmethods data analysis. The software is available as a universal appfor Windows and Mac OS X and can help you analyze all kinds ofunstructured data like interviews, articles, media, surveys, twitter,and more.

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MaxQDAScreen

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Introduction

Good Research


Collecting Data

Coding Data

Analysis Tools

Data Displays


Bibliography

Vicenc Fernandez



Components of Data Analysis


Components of Data analysis

Data Collection

Conclusions: drawing/verifying

Data Reduction

Data Display

Pre-Data Collection

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Pre-Data Collection / Research Design

I The qualitative research is beginning to focus on the studysissues, the cases to be studied, the data to be collected, andhow these data will be managed and analyzed.

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Data Collection

I There are many ways to gathering data: Interviews, writtendocuments, pictures, etc.

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Data Reduction

I Data reduction refers to the process of selecting, focusing,simplifying, abstracting, and transforming the data thatappear in written-up field notes or transcriptions.

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Data Display

I A display is an organized, compressed assembly of informationthat permits conclusion drawing and action. The mostcommon display is extended text.

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Conclusions drawing and verification

I The conclusions have also been prefigured fro the beginning

I Conclusions are also verified as the analyst proceeds.

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Research Design

I The methodology and the method.

I The conceptual framework (optional).

I The research question.

I The research purpose.

I The propositions (if any).

I The unit(s) of analysis.

I The sampling.

I The tool for getting data.

I The strategy for analysing data.

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Introduction

Good Research


Collecting Data

Coding Data

Analysis Tools

Data Displays


Bibliography

Vicenc Fernandez



Six sources of evidence

I Documentation

I Archival Records

I Interviews

I Direct Observations

I Participant-Observation

I Physical Artifacts

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Situations for di↵erent research strategies

When to Use Each Strategy?

I The type of Research Question

I The control of Behavioral Events

I The degree of focus on contemporary as opposed to historicalevents

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Situations for di↵erent research strategies

Strategy RQ Control ContemporaryExperiment How, why? Yes YesSurvey Who, what, where, No Yes

how many, how much?Archival analysis Who, what, where, No Yes/No

how many, how much?History How, why? No NoObservations How, why? No YesInterviews How, why? No Yes

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Principles of data collection

There are three principles, which are relevant to all six sources.

I Principle 1: Use multiple sources of evidence

I Principle 2: Create a database

I Principle 3: Maintain a chain of evidence

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Principles of data collectionPrinciple 1: Use multiple sources of evidence

Triangulation

I Rationale for using multiple sources of evidence

Types of triangulation

I Of data sources (data triangulation)

I Among di↵erent evaluators (investigator triangulation)

I Of perspectives to the same data set (theory triangulation)

I Of methods (methodological triangulation)

To improve the construct validity.

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Principles of data collectionPrinciple 2: Create a database

How to organizing and documenting the data collected.

I Its very di�cult to create a standard database

There are two kinds of information:

I The data or evidentiary base

I The report of the investigator

There are four kinds of components:

I Notes (to organize, categorize, and complete)

I Documents (to access)

I Tabular Materials (as quantitative data)

I Narratives (to access)

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Principles of data collectionPrinciple 3: Maintain a chain of evidence

I To increase the reliability.

I An external observer should be able to trace the steps ineither direction.

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Documentation

This type of information is take many forms and should be theobject of explicit data collection plans.

Types of documents

I Letter, memoranda, and other communiques

I Agendas, announcements and minutes of meetings, and otherwritten reports of events.

I Administrative documents proposals, progress reports, andother internal records.

I Formal studies or evaluations of the same site under study.

I Newspaper clippings and other articles appearing in the massmedia or in community newsletters.

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Archival Records

I Many times they taking form of computer files or records.

I The usefulness of these archival records will vary fromresearch to research.

I Researcher must be careful to ascertain the conditions underwhich it was produced as well as its accuracy.

I The numbers of these Archival Records should notautomatically be considered a sign of accuracy.

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Interviews

Types of InterviewI Structured Interview

I The Interview aims to explain more than understanding.I The Interviewer asks a set of questions with a predetermined

set of answers.I The Interviewee: All respondents receive the same package of

questions.I Answers: They are closed (categories box).

I Unstructured interviewI The Interview seeks to understand rather than explain.I The Interviewer asks questions without fixed pattern of

response categories.I The Interviewee: Each respondent receives his/her own set of

questions.I Answers: They are open by definition (non categories).

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ObservationsTypes of observation

Observation strategies

I Participatory directly or without participating in thephenomenon

Levels of systematization

I Fixing or without specifying the categories, groups, ...

Degree of control

I Controlling and manipulating the situation or without control

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Physical Artifacts

Physical or cultural artifact.

Physical artifacts have less potential relevance in the most typicalkind of organizational research.

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maxQDAMain Screen

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maxQDAImporting our documents

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maxQDAImporting our documents

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maxQDAPre-Importing Gathered Data

I suggest to:

I Transcribe our interviews to text.

I Describe our observations with text.

I Transform our questionnaires to text.

I Describe the physical artefacts with text.

The software allows to work with picture, pdf, MS-Word, audio,video, etc., but it’s easier to work with texts.

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maxQDATranscribe interviews

maxQDA supports the transcription of audio and video data withbasic functions.

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Introduction

Good Research


Collecting Data

Coding Data

Analysis Tools

Data Displays


Bibliography

Vicenc Fernandez



Codes and coding

After gathering all data of your research, the next step is toprocess and order all this information.

I Time: You need 3 to 6 times as much time for processing andordering the gathered data as you needed to collect it.

Two problems:

I Data overload: How I can process all information

I Data retrieval: How I can access information that I need

Coding is analysis ) Its hard and di�cult

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Codes and codingBasic Concepts

IMeaning unit: We need to explicit what we want to analyzeof the interview (e.g. Barriers, behaviours, best practices).

ICoding unit: We need to explicit how we are going to encodethe interview. We can encode by sentence, by paragraph, bytopic, by phenomenon, etc. In our research field, the mostcommon is the topic.

ICode: Of course, we need to create our code list.

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Creating codesDefinition of Code

The elements (codes) inside of the same category or super-codemust be disjunctive. The list of codes will be a table with thefollowing fields:

ILabel: Clear, Concise, close to the raw data, descriptive

IDefinition: What it means

IDescription: When the theme occurs

IInclusion and Exclusion Criteria: Passages included andexcluded in the code

IExamples: Occurrences of the code

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Codes and coding

Characteristics of codes

I Codes can be at di↵erent levels of analysis

I Codes can happen at di↵erent times during analysis

Revising codes

I Some codes decays and other codes flourish.

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Creating codesMethod

1. To create a start list of codes from the conceptual framework,research questions, hypotheses, problem areas, and other keyvariables. The start list can contain fro 12 to 60 codes.

2. An inductive approach.

3. A combination: see Lofland (1971) or Bogdan and Biklen (1992)

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Creating codesCode List: Tips

We need to avoid the nodes duplication trap. We have to create acode scheme where the last code of it.Wrong Code Scheme:

I WomenI Feelings

I PositiveI Negative

I MenI Feelings


I YouthI Feelings


Correct Code Scheme:

I GenreI WomanI Man

I AgeI ChildI YoungI Adult

I FeelingsI PositiveI Negative

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Codes and codingCheck-coding

How to check a code?

I Two people code separately 5-10 pagesI To calculate the level of reliability:

IReliability = number of agreements

number of agreements + disagreements

I If reliability is better than 70% ) OK

Final advice

I Not every piece of the notes must be coded.

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Summary of encoding

The coding is a way of forcing you to understand what is still

unclear, by putting names on incidents and events, trying cluster

them, communicating with other around some commonly held

ideas, and trying out enveloping concepts against another wave of

observations and conversations.

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Before starting to encode

Before encoding documents, its important to understand thedocument (eg. interview). So, try to summary the document injust one page.

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Let’s start to encoding

Now its time to encode the interview. Try to overlap segmentswith di↵erent codes. If you need to create a new code, do it. Andat the end, start to encode again the whole interview.

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maxQDAMain Screen

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maxQDACodes

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RQDACoding process

1. Open a file.

2. Read and think if some words are relevant to a code.

3. Apply that code to the text segment: select a code, selectthat text segment, and drag the sentence to the ”Code”.

4. Keep reading and thinking.

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maxQDAMain Screen

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maxQDACoding

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maxQDACoding

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maxQDACoding

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MemoingWhats a memo?

Its the theorizing write-up of ideas about codes and theirrelationships as they strike the analyst while coding it can be asentence, a paragraph or few pages it exhausts he analystsmomentary ideation based on data with perhaps a little conceptualelaboration.

Memos are primarily conceptual in intent.

The memo writer can:

I Aim at clarifying the idea

I Tie it to information from a case

I Di↵erentiate the idea from already existing codes.

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Memos should always be

I Dated.

I Entitled with key concepts discussed.

I Linked to particular places in the field notes, to previous caseanalysis discussions, or to case summaries.

I Coded according to the concept(s) they are about, and keptseparate from data files.

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Advices

I Give ALWAYS priority to memoing.

I Memoing should begin as soon as the first field data starcoming in.

I Keep memos ’sortable’.

I Memos are about ideas.

I Do not standardize memos formats or types.

I Memo writing is fun.

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maxQDAMemoing

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maxQDAMemoing

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Introduction

Good Research


Collecting Data

Coding Data

Analysis Tools

Data Displays


Bibliography

Vicenc Fernandez



Analysis ProcessStep 1

Analysis case-by-case:

1. Take one case

2. Analyse the case

3. Display the case

4. Write the results of the case with words

5. Confirm the results of the case

6. Take another case, and start the whole process.

7. If you discover something new, re-analyze the previous cases.

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Tactics for Generating MeaningPatterns

We need to find repetitions (patterns) which:

I add new dimensions to the phenomenon

I confirm previous propositions

I contradict an established theory

I help to generate hypothesis

I deepen our understanding

There are many techniques/tactics to analyse the interview...

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Tactics for Generating MeaningRelationships

Noting Relationships Between Variables

I A+, B+

I A+, B-

I A", B "I A", B #I A", then B "I A", then B #

Findings Intervening Variables

I moderating e↵ect

I mediating e↵ect

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Tactics for Generating MeaningI Noting Patterns, ThemesI Seeing Plausibility: Plausibility and intuition are the

underlying bases, and are not to be sneered at.I Clustering: Classes, categories and bins.I Making Metaphors: They are usefulness because it is

necessary a certain level of abstraction of data, and they canhelp you to relate to theory.

I CountingI Making Contrasts/Comparisons: Compare everything. All

time. All places.I Partitioning Variables: Try to divide complex variables, or

variables with rare behavior.I Subsuming Particulars Into the General: Actions, Events,

States,I Factoring: Factor analysis

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maxQDAAnalysis Tools

The analysis is something you have to done manually. maxQDAgives us some tools in order to summary (in a di↵erent ways) allcontent we have collected. This maxQDA tools simplifies theanalysis, but at the end the researcher is the key of the analysis.

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maxQDAAnalysis Tools

Some interesting tools are:

I Table Codes versus Codes, where we can see the number oftext segments that have been coded at the same time for twocodes.

I Table Files versus Codes, where we can see the codes thathave been used in each file.

I Retrieved text segments that have been coded by acombination of codes.

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maxQDATable Codes versus Codes: Code Relations Browser

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maxQDATable Files versus Codes: Code Matrix Browser

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maxQDARetrieved text segments

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Introduction

Good Research


Collecting Data

Coding Data

Analysis Tools

Data Displays


Bibliography

Vicenc Fernandez



Steps for Analyzing Qualitative Data

Analyses case-by-case:

1. Take one case

2. Analyse the case

3. Display the case





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Displays

Two types of displays:

I Matrices

I Networks

Two types of paradigm:

I Variable-oriented approach: Relations among well-definedconcepts

I Process-oriented approach: Set of events in a specific casecontext over time.

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DisplaysObjectives

Description:

I Making complicated things understandable by reducing themto their component parts

Explanation

I Making complicated things understandable by showing howtheir component parts fit together according to some rules.

CausalityI There is no precise demarcation between general explanation

and causality. Determining causality:I Temporal precedence: A precedes B.I Constant conjunctions: When A, always B.I Contiguity of influence: A plausible mechanism links A and B.

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List of displays

Miles & Huberman (1994):

I Within-Case Displays: Exploring and Describing

I Within-Case Displays: Explaining and Predicting

I Cross-Case Displays: Exploring and Describing

I Cross-Case Displays: Ordering and Explaining

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1. Take one case

2. Analyse the case

3. Display the case





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Write the results of the case with words

Try to explain your displays with words using references to theencoded documents. All displays need explanations.

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Verification the results

Now, we need to analyze the robustness of the display. The idea isvery simple, change di↵erent parts of the display and try to explainit with the current data you have. If you can do it, the displaydoesnt work and you have to improve it.

This process is iterative.

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1. Take one case

2. Analyse the case

3. Display the case




7. If you discover something new, re-analyze the previous

cases.

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Cross-case Analysis:

1. Take the displays and the results of some cases (according toyour attributes). We’ll call cross-cases.

2. Analyse the cross-case

3. Display the cross-case

4. Write the results of the cross-case with words

5. Confirm the results of the cross-case

6. Take another cross-case, and start the whole process (if it’s).

7. If you discover something new, re-analyze the previouscross-cases.

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Introduction

Good Research


Collecting Data

Coding Data

Analysis Tools

Data Displays


Bibliography

Vicenc Fernandez



Main IDEA...

Clarity, Force and Ease

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General structure for researchers

1. Statement of the problem

2. Conceptual framework

3. Research questions

4. Methodology

5. Data Analysis

6. Discussion (and propositions)

7. Conclusions

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Structures


Structures

Events, anecdotes, episodes,… Variables

50-70% 30-40%

Remember: the reader needs to be able to understand the whole research process, and to replicate the research.

Remember: the reader needs to be able to understand the whole

research process, and to replicate the research.

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Example of guide...

American Psychological Association

I Publication Manual of the American PsychologicalAssociation, Sixth Edition.

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Final TIPS

Why is reproducibility so important? Because it is the only thingthat an investigator can guarantee about a study.

Contrary to what most press releases would have you believe, aninvestigator cannot guarantee that the claims made in a study arecorrect (unless they are purely descriptive).

So reproducibility is important not because it ensures that theresults are correct, but rather because it ensures transparency andgives us confidence in understanding exactly what was done.

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Final TIPS

For this reason, its very, very, very important to record all stepsand decisions that we have followed during the data analysis. Itsthe only way to justify our results. For this reason, I suggest thecreate a research diary where we take notes of all our decisions,changes, ideas, explanations (with dates) during the research.

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Introduction

Good Research


Collecting Data

Coding Data

Analysis Tools

Data Displays


Bibliography

Vicenc Fernandez



BibliographyBasic Literature

I Miles, M. B., & Huberman, A. M. (1994). Qualitative dataanalysis, 2nd ed. Newbury Park, Cal.: Sage.

I Yin, R.K. (1984). Case study research: Design and methods.Berverly Hills, CA: Sage.

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BibliographyComplementary Literature

I Bogdan, R; Biklen, S.K. (1992) Qualitative Research For Education,Boston: Allyn and Bacon.

I Corbin, J.; Strauss, A. (1990). Grounded theory research: Procedures,canons, and evaluative criteria. Qualitative Sociology, 13, 3-21.

I Glaser, B.G.; Strauss, A.L. (1967). The Discovery of Grounded Theory.Strategies for Qualitative Research. Sociology Press.

I Lofland, J. (1971). Analyzing social setting: A guide to qualitativeobservation and analysis. Belmont, CA: Wadsworth Publishing Co.

I Patton, M.Q. (1990). Qualitative evaluation and research methods.Newbury Park, CA: Sage.

I Ruiz Olabuenaga, I. (1996). Metodologia de la investigacion cualitativa.Bilbao: Universidad Deusto.

I Sandoval, C.A. (1996). Investigacion cualitativa. ICFES: Bogota.

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