P&B Chapter 25 Flashcards

1
Q

T/F: Mixed Methods research is the collection of quantitative and qualitative data but also the integration of the two at the same stage of the research process

A

True

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2
Q

Conclusion generated by integrating inferences obtained from the results of the qualitative and quantitative strands of an MM study

A

meta-inference

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3
Q

Name the 5 advantages of a MM approach

A
  1. Complementarity
  2. Practicality
  3. Incrementality
  4. Enhanced Validity
  5. Collaboration
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4
Q

This advantage describes how qualitative and quantitative approaches use words and numbers which are the two fundamental languages of human communication - using the two approaches together avoids limitations of a single approach

A

Complementarity

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5
Q

This advantage describes how phenomenon are complex and it is better to not have one’s hands tied by rigid adherence to a single approach- MM research answers questions most other research cannot

A

Practicality

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6
Q

This advantage describes how progress on a topic relies on feedback loops; building this into a study simultaneously address exploratory and confirmatory questions

A

Incrementality

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7
Q

This advantage occurs because a hypothesis or model is supported by multiple and complementary types of data - researchers can be more confident in their results

A

Enhanced validity

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8
Q

This advantage describes the opportunities for encouragement between quantitative and qualitative researchers working on similar problems

A

Collaboration

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9
Q

The paradigm of _____ is most often associated with MM research

A

Pragmatism - research question should drive the inquiry; the research question is more important than the methods used

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10
Q

Describe four broad types of research that is especially well suited for MM research

A
  1. concepts are new and poorly understood - need for qualitative exploration before more formal methods can be used
  2. findings from one approach can be greatly enhanced with a second source of data
  3. neither approach is adequate in itself in addressing the problem
  4. quantitative results are puzzling and difficult to interpret- qualitative can help explain
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11
Q

Name the specific applications where MM research has made important contributions

A
  1. Instrumentation (researchers developing structured instruments)
  2. Intervention development
  3. Hypothesis generation and testing
  4. Explication
    Theory building, testing, and refinement
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12
Q

T/F: MM research often has at least two research questions, each which requires a different type of data and approach

A

True

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13
Q

Name the three key decisions in MM research

A
  1. Sequencing
  2. Prioritization
  3. Integration
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14
Q

When two types of data are NOT collected at the same time

A

sequential

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15
Q

When the two types of data are collected at the same time

A

concurrent

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16
Q

Deciding whether or not to emphasize one type of research over the other in a MM study

A

Prioritization- one approach is often given priority

17
Q

Concerns how the two types of data in MM research will be combined

A

Integration

18
Q

Name the four (most common) basic designs in MM research

A
  1. Triangulation
  2. Embedded designs
  3. Explanatory
  4. Exploratory
19
Q

Purpose of this design is to obtain different, by complimentary, data about the central phenomenon under study; qual and quan data are collected simultaneously and with equal priority; overall goal is to converge on the “truth” about a problem by allowing the weaknesses of one approach be offset by the strengths of the other

A

Triangulation design

20
Q

Name the three variants under the triangulation design

A
  1. Convergence (data collected in parallel; results of two separate analyses are compared and contrasted)
  2. Data transformation (qual data is transformed into quan data before data comparison)
  3. Multilevel (using different methods at different levels of a complex system - ex. hospital system)
21
Q

In this design - one type of data is used in a supportive capacity in a study based primarily on the other data type - either qual or quan can be dominant; sequencing is often concurrent but can be sequential

A

Embedded design

22
Q

Sequential designs with quantitative data collected in the first phase, followed by qualitative data collected in the second phase - either data can be given a stronger priority; qual data from second phase helps to build on quantitative data from first phase; straightforward and easy to describe and can be done by single researcher

A

Explanatory design

23
Q

Sequential MM designs, but qualitative data are collected in the first phase; findings from initial phase are used in a second, quantitative phase

A

Exploratory design

24
Q

Sampling: In this type of relationship, the two strands are completely different, although they are usually drawn from the same or a similar population; can occur in either concurrent or sequential designs and with any of the prioritization schemes

25
Q

Sampling: In this type of relationship, participants in the qualitative strand are a subset of the participants in the quantitative strand; very common approach in MM research

26
Q

Sampling: In this type of relationship, samples are selected from different levels of a hierarchy- usually from different but related populations

A

multilevel

27
Q

What are the decisions that need to be made when analyzing MM data?

A
  1. What is the overall goal of the study?
  2. Will integration occur at the analysis stage or the interpretation stage
  3. What will be the unit of analysis?
  4. Is the focus of the study more case oriented or more construct oriented?
  5. Will either type of data be converted or transformed?
  6. Will direct comparisons be made between the qualitative and quantitative data - and if so, at what level will the comparisons be made?
  7. Will integration involve the use of specialized software?
28
Q

T/F: Quantitative data can be qualitized and qualitative data can be quantitized

29
Q

T/F: Matrices are often used in analytic integration of qualitative and quantitative data (meta-matrix)

30
Q

Overarching criterion for evaluating the quality of conclusions and interpretations made on the basis of mixed methods findings

A

Inference quality

31
Q

Degree to which the mixed methods conclusions can be applied to other similar people, context, settings, time periods, and theoretical representations of the phenomenon

A

Inference transferability

32
Q

Sampling: In this type of study with sampling, the same people are in both components of the study

33
Q

Quantitative data are analyzed using statistical techniques while qualitative are analyzed using qualitative analysis methods; findings from two separate analysis are synthesized for overall interpretation; focus on comparing the two types of findings

A

Interpretive integration