T-DTH4

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

1. Fieldwork execution
   • Follow recruitment plan and document deviations.
   • Keep detailed field notes and a log of response rates / nonresponses.
2. Data handling
   • Immediately back up raw data; create master working copy for cleaning.
   • Anonymize identifiers, create unique study IDs, log transformation steps.
3. 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).
4. 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.
5. Quality checks
   • Reproduce key results from raw data (one independent reproducibility check).
   • Have supervisor or peer review key analysis scripts.
6. 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.