You are an expert M&E evaluator. Generate a methods section that scores Excellent (5) on every dimension of the Methods Section Quality rubric for the situation described below.
QUALITY REQUIREMENTS:
Design Justification: Name the overall design and justify it with a rationale tied to the evaluation purpose and questions. Make explicit why this design and not an alternative.
Data Collection Detail: For each instrument, state its purpose, format, length, and respondent type. Document sampling (frame, size, selection method, response rates). Describe procedures (training, piloting, data collection period, mode). Provide enough detail for a competent reader to assess rigor.
Analysis Approach: For each data type, specify the analytic approach. Quantitative: descriptive statistics, inferential tests, software, missing data handling. Qualitative: coding approach (framework or grounded), software, inter-rater process. Mixed-methods: integration strategy and sequencing. Make traceable how raw data became findings.
Quality Assurance: Describe validity safeguards (triangulation, instrument validation, pilot testing), reliability safeguards (inter-rater agreement, transcription protocols, audit trail), and ethical safeguards (consent, anonymization, safeguarding, sensitive-topic handling, data security, IRB or equivalent).
Reproducibility: Reference or annex instruments. Document sampling and analytic decisions. Note deviations from the original plan with rationale. Make replication or critique possible from this section alone.
FORMAT: Present as a numbered methods section: (1) Design and Rationale, (2) Sampling and Participants, (3) Data Collection Instruments and Procedures, (4) Analysis Approach by Data Type, (5) Quality Assurance and Ethics, (6) Limitations and Deviations from Plan.
SITUATION BRIEF:
[Paste the evaluation purpose and questions, design choice, data sources collected, sampling decisions, instruments used, analytic approach, ethical procedures, and any deviations from the original plan here]
Quality bar: The result must meet these criteria. It will be reviewed against them afterwards.
- Design Justification: Whether the overall design is named and justified (why this design, not an alternative), with the link to the evaluation purpose and questions made explicit rather than assumed.
- Data Collection Detail: Whether instruments, sampling, and procedures are described in detail usable by a reader who wants to assess, replicate, or critique the data collection, not merely listed at a high level.
- Analysis Approach: Whether the analytic approach for each data type (quantitative, qualitative, mixed) is specified with enough detail that the reader can understand how raw data became findings.
- Quality Assurance: Whether validity, reliability, and ethical safeguards (triangulation procedures, inter-rater checks, member checks, consent, anonymization, safeguarding) are described rather than assumed.
- Reproducibility: Whether a competent reader could replicate or critique the study from the methods section alone, with all key procedural decisions documented and instruments referenced or annexed.
Anything still in [brackets] is not known yet: ask me, or mark it clearly in your answer.