Mixed Methods Design

Mixed Method Assumptions
Pragmatists
Explain something
Truth is “what works”
Researcher and outcomes

Paradigm: Pragmatists
Meaning lies in the practical outcome
Value of research is practical application
Explanatory hypotheses…..a middle ground between straight deductive hypothesizing and inductive theory- building to promote practical use
Knowledge is an instrument for adapting to reality and controlling it (via solutions)
Real-life problems
Truth: Does it work?

Mixed Method Research: Method
the collection and analysis of quantitative and qualitative data in a single study. Data can be collected at the same time or in phases and integrated at one or more stages in the research process

Mixed Method Research: Premise
Mixing quantitative and qualitative approaches allows us to better understand the problem than each approach alone and develop a practical solution

Mixed Method Research: Data Collection
Combine data from quantitative and qualitative research

Mixed Method Research: Data Analysis
Combine data analysis outcome:

Mixed Method: Quantitative Data Analysis for:
Describing, comparing, inferring and predicting

Mixed Method: Qualitative Data Analysis for:
Uncovering, meaning, understanding persepectives

Both approaches Quant and Qual follow
Standards of Rigor

Advantages to Mixed Method Approach
Enables a stronger understanding and interpretation–Explain quantitative data
Addresses limitations of each method
Triangulates information
Gain various perspectives (compare)
Practically “tests” a theory
Increases Validity of your Outcome

Core Characteristics of Mixed Method Approach
Develop research questions reflecting need for both QUAL and QUAN approaches
Collect and analyze QUAL and QUAN data using rigorous methods
Integrate data at the same time- OR so they build upon each other
Identify a priority (if any)
Communicate unique interpretation

Mixed Method Designs (4)
Triangulation
Explanatory
Exploratory
Embedded

Triangulation (Concurrent) Design
Information from different perspectives

Explanatory Design
QUAN Data –> QUAL Data –> Final Interpretation

Exploratory Design
QUAL Data –> QUAN Data –> Final Interpretation

Exploratory Examples
Explore a phenomenon
Develop instrument
Develop a theory

Embedded Designs
Qual
Quan
One data set provides a secondary role

Comparision of Mixed Method Approaches

Qualitative Research Question
Broad central question with more specific subquestions
Verbs: Discover, explore, understand

Quantitative Research Question
Narrow question
Hypothesis about relationship among variables
Determine, relate, impact, rate, effect, compare