An Overview of Qualitative Research Methods Presented by Johnnie Daniel, Ph.D., J.D. Department of...

An Overview of Qualitative Research Methods

Presented by Johnnie Daniel, Ph.D., J.D.Department of Sociology and [email protected]

for the

RESPONSIBLE CONDUCT RESEARCH WORKSHOPGRADUATE SCHOOL, HOWARD UNIVERSITY

FEBRUARY 13, 2013

Introduction

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Purpose of presentation

Provide an introduction to qualitative research methods

Provide descriptions of the differences between qualitative research and quantitative research

Provide a basis for further study and investigation of qualitative research

Encourage the use of qualitative research methods

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Learning objectives

At the end of this presentation you should be able to: Distinguish between qualitative research and quantitative

research in carrying out the following activities: Problem formation Research design development Selection of data sources Data collection Data analysis Conclusion and report writing

Identify and distinguish the major types of qualitative research designs

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What are the differences between qualitative research and quantitative research?

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Qualitative research is research primarily involving the collection and analysis of non-numerical data

On the other hand, quantitative research is research primarily involving the collection and analysis of numerical data

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Both follow the same major steps in carrying out a research study

However, due to the nature of the data collected, important differences in how these steps are executed

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Major Steps in Conducting Research

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Conclusion / Report Writing

Problem formulation

Research design development

Data analysis

Selection of data sources

Datacollection

Problem formation:

Theory development Exploratory purpose Description of participants Comparison of participants Create in-depth

descriptions and understandings of characteristics

Hypothesis and theory testing

Description of population Comparison of categories

within the population Create in-depth descriptions

and understanding of relationship among variables

Qualitative Research Quantitative Research

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Problem formation:

Elucidate findings of quantitative research

Verify the presence of phenomena

Purpose to research is to understand a problem

Verify findings of qualitative research

Identify the causes of phenomena

Purpose of research is to explain and predict the existence of a problem


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Problem formation:

Understand from the point of view of the participants

Interpret experiences and meaning s

Discover theme and relationships

Provide words for closed questions

Understand relationships among variables


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Problem formation:

Discovery and identification of new thought and understandings

Purpose to discover ideas Exploratory research

Verification of theory, predictions

Purpose to test hypotheses Conclusive research


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Problem formation:

Program aims at individual outcomes

Theory developed during study

Data precede theory Complex patterns of

interactions among variables not investigated

Program aims at common outcomes

Theory developed a priori Theory precedes data Complex patterns of

interactions among variables may be investigated


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Research design development:

Participant observation Focus group research Case studies In-depth interviews Typically no comparison

groups Research design modified

as it is implemented

Survey Numerical databases Comparison groups Research design

predetermined


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Selection of data sources (study participants)

Nonprobability sampling Availability sampling Purposive sampling

Small n Data saturation, sequential

sampling

Probability sampling Simple random

sampling Stratified sampling

Large n Sample size predetermined


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Major Types of Purposive Sampling

Selection criteria: Elements’ fit or lack of

fit with central tendency

Selection criteria: Variability of elements

Selection criteria: Theory, model

development, and hypothesis testing

Selection criteria: Judgment, reputation,

or specialized knowledge

Confirmatory sampling Judgment samplingDisconfirming sampling Subjective sampling

Homogeneous Negative case samplingBellwether case sampling

Typical case sampling sampling Theoretical samplingReputational sampling

Modal instance sampling Critical case sampling Politically important casesSystematic matching sampling Expert samplingCase control sampling Informant samplingConsecutive sampling

Deviant case sampling Maximum variation samplingRare element sampling Heterogeneity samplingExtreme case sampling Diversity samplingIntensity case samplingDichotomous case samplingOutlier sampling

Data collection:

Observation Asking primarily open-

ended questions Scalar items seldom used Unobtrusive data collection Data: words, pictures,

behavior Greater ethical issues

Asking primarily closed-ended questions

Scalar items primarily used Statistical databases Data: numbers Fewer ethical issues


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Data collection:

Researcher interacts at personal level with respondents

Personal values made explicit

Flexible Unstructured

Researcher seeks to keep personal values, beliefs, and biases separate

Personal values avoided Not flexible Structured


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Data collection:

Researcher must be able to fit-in with events/people studied

Data collection environment not controlled

Same questions not necessarily asked to all participants

Data collector may improvise

Researcher can be distant from events/people studied

Data collection environment controlled

Same questions asked to all participants

Data collector should not improvise


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Data collection:

Subjectivity focus Adaptive data collections Exact replication not

possible Theory is “data driven” Probing Information per respondent

is substantial

Objectivity focus Predetermined data

collection Exact replication possible Data are “theory driven” Limited probing Information per respondent

varies


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Data collection:

Hardware: tape recorders, video, cameras

Training of researcher: psychology, sociology, consumer behavior

Conversation, unstructured

Hardware: computers, telephone

Training of researcher: psychology, sociology, consumer behavior, statistics

Structured observation, interviews, questionnaires


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Data collection:

Contextual variables critical to study

Collect verbatim responses More limited to collection

of data on current patterns More flexible

Contextual variables not necessarily critical to study

Collect responses to structured items

Less limited to collection of data on current patterns

Less flexible


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Data analysis:

Limited statistical analysis Inferential statistics are

generally irrelevant Lack of ability to control

for extraneous variables Results cannot be

generalized

Basic to advanced multivariate statistical analyses

Inferential statistics are generally essential

Results are generalizable based on inferential statistical analyses


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Data analysis:

Lack of ability to control for extraneous variables

Data processing and analysis time consuming

Varied analyses Focus on themes and

meanings

Potential to control for extraneous variables

Data processing and analysis not as time consuming

Standardized analyses Focus on trends,

comparisons, predictions, explanations


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Data analysis:

Inductive analyses “Thick descriptions” Validity based on honesty,

richness, authenticity, depth, scope, subjectivity, strength of feeling, catching uniqueness, idiographic statements

Deductive analyses Control of extraneous

variables Validity based on

objectivity, generalizability, replicability, predictability, controllability, and nomothetic statements


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Data analysis:

No testing of null hypotheses

No confidence intervals Meaning rather than

numeric descriptions sought

Null hypothesis testing Confidence intervals Numeric descriptions

sought


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Conclusions / report writing:

Focus on: Credibility Dependability Transferability Confirmability

Focus on: Internal validity Reliability, stability External validity Objectivity


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Conclusions based on understandings, insight

Conclusions are subjective, speculative

Conclusions based on statistical analyses

Conclusions stated in context of statistical degree of accuracy


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Replications lead to tentative generalizations

Predicated on the assumption that each individual, culture, setting is unique

Generalizations based on probabilities

Assume “law” or “trends” may be identified


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Reports are longer, written in narrative form and published in the form of books or monographs

Narrative descriptions

Reports are commonly reported in journals and only 5-15 pages in length

Statistical descriptions


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What are the major types of qualitative research designs?

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Focus Groups

Qualitative Research Designs

EthnographyEthnography

ObservationObservation

Qualitative Data

Qualitative Data

Projective TechniquesProjective

Techniques

Case Studies

Action Research

Grounded Theory

In-depthInterviews

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EXHIBIT 5.2 Common Qualitative Research Tools

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EXHIBIT 5.2 Common Qualitative Research Tools (cont’d)

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Choosing a Qualitative Method

Participant characteristics

Participant characteristics

Researcher characteristics

Researcher characteristics

FactorsFactors

Ethical concernsEthical

concerns

Resources

Nature of topic

Purpose of study

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Challenge: Mixed-Methods Research Designs

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Mixed-Methods Research Design

Quantitative

Research Design

Qualitative

Research Design

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