Goal: Execute fieldwork/data collection, analyze data according to plan, and prepare Chapter 5 draft with interim results and interpretation.
Key deliverables (end of T-DTH4)
- Cleaned dataset or full set of qualitative transcripts.
- Analysis scripts or coding frameworks (NVivo/Atlas, R/Stata/SPSS syntax).
- Draft Chapter 5: Data Analysis, Results, and Discussion.
- Evidence of data quality checks and a short methods-in-practice appendix (what happened in the field).
- Preliminary conference-style 10–12 slide presentation of findings.
Step-by-step checklist
- Fieldwork execution
- Follow recruitment plan and document deviations.
- Keep detailed field notes and a log of response rates / nonresponses.
- Data handling
- Immediately back up raw data; create master working copy for cleaning.
- Anonymize identifiers, create unique study IDs, log transformation steps.
- Analysis
- Quantitative: run descriptive stats, test assumptions, run planned models, sensitivity analyses.
- Qualitative: code transcripts, develop themes, use memoing and iterative coding reliability checks.
- Mixed methods: show how quantitative and qualitative findings integrate (convergence, complementarity, divergence).
- Write Chapter 5
- Present methods applied, response rates, profile of sample.
- Present results clearly (tables/figures) and relate back to hypotheses/theory.
- Discussion: interpret, compare with literature, explain unexpected findings.
- Quality checks
- Reproduce key results from raw data (one independent reproducibility check).
- Have supervisor or peer review key analysis scripts.
- Prepare presentation
- 10–12 slides: background, methods, main results, interpretation, limitations, next steps.
Analysis checklist (quick)
- Are assumptions for tests met? Y/N (if N, note alternatives).
- Are missing data patterns analyzed and addressed?
- Are effect sizes and confidence intervals reported, not just p-values?
- Are qualitative quotes linked to participant codes and contextualized?
Quality assessment rubric (for T-DTH4)
- Data integrity & reproducibility (30%)
- Correctness of analysis (30%)
- Clarity of result presentation (20%)
- Depth of interpretation & linkage to theory (15%)
- Documentation of field issues & adjustments (5%)
Common pitfalls & mitigations
- Pitfall: Poor response rates → mitigation: use follow-ups and document nonresponse bias.
- Pitfall: Overfitting/excessive post-hoc analyses → mitigation: label exploratory analyses clearly.
- Pitfall: Losing context in qualitative coding → mitigation: keep memos and participant context sheets.