Week 11 Lecture: Mixed-methods research Flashcards

1
Q

Mixed-methods research

=

A

= mixing quant and qual

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2
Q

Types of mixed-methods research design

4

A
  • sequential = quant –> qual or vice versa
  • concurrent/convergent = same time, one study
  • embedded/nested = one dominant, one embedded
  • transformative = aim for world change while doing research
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3
Q

Modes of Mixed-Methods Research Analysis

3

A
  • triangulation
  • complementary
  • iterative
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4
Q

Mixed Methods Research (Johnson, Onwuegbuzie and Turner, 2007)

“”

A

“a type of research in which a researcher or team of researchers combine elements of qualitative and quantitative research approaches (e.g. use of qualitative and quantitative viewpoints, data collection, analysis, inference techniques) for broad purposes of breadth and depth of understanding and corroboration”

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5
Q

Quantitative methods of inquiry

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A

= ideal for measuring pervasiveness of “known” phenomena and central patterns of association, including inferences of causality

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6
Q

Qualitative methods of inquiry

=

A

= allow for identification of previously unknown processes, explanations of why and how phenomena occur, and raneg of effects

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7
Q

Mixed methods inquiry

=

A

= intentional collection of both quantitative and qualitative data and the combination of strengths of each to answer research questions

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8
Q

Mixed Methods History

3

A
  • 1980s: Paradigm Wars = 2 fundamentally different ways of viewing knowledge, evidence, what is valuable to health (quant vs QUAL)
  • 1991: Developed procedures for designs of mixed methods, including visualisation of design and notation procedures (Morse, 1991)
  • 1997/8: need to formalise distinct design in books so research can be published, leaders in field: Green & Caracelli 1997, Tashakkori & Teddlie 1998, Cresswell & Plano-Clark, also set up conference and journal = Journal of Mixed Methods Research
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9
Q

Reasons for using mixed methods (arguments)

6

A
  • insufficient argument = either quant or QUAL insufficient alone
  • multiple angles argument = quant and QUAL provide different perspectives
  • more-evidence-the-better argument = combined quant and QUAL provides more evidence
  • community of practice argument = preferred approach within a scholarly community
  • eager-to-learn argument = latest methodology
  • “its intuitive” argument = it mirrors real life
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10
Q

Situations in which Mixed Methods is needed

3

A
  • developing context-specific instruments
  • explain results
  • evaluation processes
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11
Q

Integration strategies for mixed-methods designs

4

A
  • convergent designs = different methods, same time same study (quan –> <— qual)
  • exploratory sequential design = explore issues –> find patterns. extent (qual –> quant)
  • explanatory sequential design = find trends –> explain meaning (quant –> qual)
  • concurrent = one dominant, one embedded for better udnerstanding
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12
Q

Connected/sequential integration

=, 2

A

= one data type builds on another
- exploratory
- explanatory

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13
Q

Embedded mixed-methods design

=, 3

A

= plays supportive role or one type or both types of data, intent of enhancing design
- concurrent or sequential data collection
- 1 or 2 phases
- usually have primary and secondary questions, different methods for each

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14
Q

Mixing or linking quant/qual data

3

A
  • converge data: qual –> results <– quant
  • connect data: qual –> quant –> results
  • embed data: [quant (qual)]
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15
Q

Triangulation Design (concurrent/convergent)

=, 1

A

= priority to both quant and qual evenly, collected concurrently, compare results from quant and qual to determine similarity of results
- in convergent mixed methods designs

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16
Q

Steps for Conducting a Mixed Methods Study

7

A
  1. Determine if mixed methods is relevant + feasible
  2. Identify a ratinale for a mixed methods study
  3. Identify the type of design/s + data collection method/s
  4. Develop quantitative and qualitative research questions
  5. Collect quant and qual data
  6. analyse data seperately or concurrently
  7. Write report as 1 or 2-phase study
17
Q

To conduct mixed methods, need:

2

A
  • minimum competency
  • methodoloical bilinguilism = know jargon of both sides
    • glossary of shared knowledge
18
Q

Evaluation of mixed emthods design

4

A
  • utility and justification for necessity in answering RQ
  • each section adhere to rigour of approach + rigour of other sections
  • team capacity
  • mode of data analyses appropriate to mixed methods design
19
Q

Modes of analysis in mixed methods

=, 3

A

= point at which data is brought together, depends on intended interaction between qual and quant data
- a priori
- emergently
- at end

20
Q

Caution in mixed methods analysis

3

A
  • common standards of quality/rigour
  • misread/mistreat data in merging
  • misread/mistreat in understanding level of inference that can be drawn
21
Q

Iterative/connecting analyses

=, 2

A

= data integration through “connecting” (iterative)
- in sequential studies
- one type of data builds upon another (e.g. quant findings –> identify qual participants)

22
Q

Complementary Analyses

=, 4

A

= analyses remain within qual or quant approach, based on drawing on both sets of analyses to make sense of arena –> “rounded”/”complete” picture
- reciprocity in building understanding
- also called: triangulation, brickolage
- in convergent mixed methods
- used throught studies from sampling –> final analyses

23
Q

Three Principle Purposes of Classical Model of Mixed Methods

A
  1. Illustration
  2. convergent validation (triangulation
  3. development of analytic density/richness
24
Q

Triangulation

=, 2

A

= combining/merging different sorts of data against theoretical perspectives applied to data
- perspectives on equal footing
- allow principal surplus of knowledge

25
Q

Critical Appraisal of Protocols

6

A

quality of:
- rationale for choice of mixed methods design
- design
- adherance to respective standards of quant and qual research
- adherance to standards for data analysis in mixed methods
- quality of analytic integration
- quality of interpretation and inference