Mixed Methods Integration Tool
A comprehensive mixed methods integration tool for managing complex research projects that combine quantitative and qualitative approaches. Support for 6 major mixed methods designs: convergent parallel, explanatory sequential, exploratory sequential, embedded, transformative, and multiphase. Create and manage quantitative components (surveys, experiments, secondary data, quasi-experiments, correlational studies) with sample sizes, variables, analyses, and findings. Create and manage qualitative components (interviews, focus groups, observations, case studies, ethnography, document analysis) with participants, data sources, themes, and findings. Define integration points between quantitative and qualitative components using 5 integration types: triangulation, complementary, expansion, explanation, and development. Document integration rationale, strategies, and insights for each integration point. Synthesize overall findings and mixed methods inferences. Track total participants across all components. Export comprehensive mixed methods reports to formatted text or JSON. Perfect for dissertation research, complex evaluation studies, implementation research, and advanced mixed methods projects.
Key Features
- Project title and setup
- 6 mixed methods designs: convergent, explanatory sequential, exploratory sequential, embedded, transformative, multiphase
- Design descriptions and guidance
- Research question documentation
- Quantitative components management
- 5 quantitative types: survey, experiment, secondary data, quasi-experiment, correlational
- Sample size tracking
- Variables documentation
- Statistical analyses tracking
- Quantitative findings
- Quantitative limitations
- Qualitative components management
- 6 qualitative types: interviews, focus groups, observations, case study, ethnography, document analysis
- Participants tracking
- Data sources documentation
- Themes identification
- Qualitative findings
- Qualitative limitations
- Integration points system
- 5 integration types: triangulation, complementary, expansion, explanation, development
- Quantitative-qualitative linkage
- Integration rationale documentation
- Integration strategy specification
- Insights from integration
- Mixed methods synthesis
- Overall findings synthesis
- Mixed methods inferences
- Meta-inferences documentation
- Convergence analysis
- Divergence analysis
- Complementarity assessment
- Add/edit/delete components
- Add/edit/delete integration points
- Component-specific management
- Integration validation
- Export to formatted text
- Comprehensive report generation
- Export to JSON for backup
- Import from JSON
- Browser localStorage persistence
- No login required
- Statistics dashboard
- Total quantitative components
- Total qualitative components
- Total integration points
- Total participants (quant + qual)
- Synthesis tips and guidance
- Integration best practices
- Responsive design
Share This Tool
This tool is 100% free and requires no login
Loading tool...
This may take a few seconds
Frequently Asked Questions
What is the difference between convergent and sequential mixed methods designs?
Convergent (parallel) designs collect and analyze quantitative and qualitative data simultaneously, then integrate findings to compare, contrast, or triangulate results. Sequential designs conduct one phase first (e.g., quantitative survey), use those results to inform the second phase (e.g., qualitative interviews), allowing one dataset to build on or explain the other. Choose convergent when you want complementary perspectives on the same phenomenon collected at once, and sequential when one phase needs to inform the design or sampling of the next phase.
How do I integrate quantitative and qualitative data in mixed methods research?
Integration occurs through five main strategies: (1) Triangulation - comparing findings to see if they converge, (2) Complementary - using findings from one method to elaborate or illustrate findings from the other, (3) Expansion - examining different aspects of the phenomenon with each method, (4) Explanation - using one method to explain surprising findings from the other, (5) Development - using one method's findings to develop instruments or sampling for the other. This tool helps document integration points, strategies, and insights systematically.
Do I need equal emphasis on quantitative and qualitative components?
No - mixed methods studies can have equal status (QUAN+QUAL), quantitative priority (QUAN→qual), or qualitative priority (QUAL→quan). Priority depends on your research questions, disciplinary norms, and available resources. Some studies use a large quantitative component with small qualitative follow-up for explanation. Others use substantial qualitative work with limited quantitative measurement. Document your design choice and justification in your methodology. This tool tracks both components regardless of relative emphasis.