You are an expert M&E data analyst. Generate a disaggregation plan and supporting language that scores Excellent (5) on every dimension of the Disaggregation Quality rubric for the program or study described below.
QUALITY REQUIREMENTS:
Disaggregation Plan Completeness: Specify standard disaggregations (sex, age where applicable). Add context-relevant disaggregations (disability, geography, vulnerability category, beneficiary type) with rationale for each. Apply disaggregation to all key indicators, not a selected few.
Method-Disaggregation Alignment: Size the sample for planned sub-group comparisons. Ensure each instrument actually collects the disaggregation variables. Use a sampling method that preserves sub-group representation. Operationalize each category the same way across all instruments.
Analysis Disaggregation: Specify disaggregated analyses. Plan significance testing or pattern comparison for sub-group differences. Include intersectional analysis where relevant. State how small sub-groups will be handled.
Reporting Disaggregation: Report disaggregated data in the main text and tables. Use visualizations that surface sub-group differences. Describe patterns in narrative. State explicitly where disaggregation is not feasible.
Use of Disaggregated Data: Write findings that reference disaggregated patterns. Tailor recommendations to sub-group findings. Reference disaggregated evidence in decisions. Carry equity gaps through to next steps.
FORMAT: Present as a numbered plan: (1) Disaggregation Categories with Rationale, (2) Method and Sample Alignment, (3) Analysis Plan, (4) Reporting Plan, (5) Use and Decision Linkage.
PROGRAM BRIEF:
[Paste the program description, target population, key indicators, intended decisions, and any context constraints here]
Quality bar: The result must meet these criteria. It will be reviewed against them afterwards.
- Disaggregation Plan Completeness: Whether standard disaggregations are specified, context-relevant disaggregations are added, the rationale for category choice is documented, and the plan covers all key indicators rather than being selectively applied.
- Method-Disaggregation Alignment: Whether sample size supports planned disaggregation, the data collection method captures disaggregation variables, the sampling method preserves sub-group representation, and categories are operationalized consistently across instruments.
- Analysis Disaggregation: Whether the analysis plan specifies disaggregated analyses, sub-group differences are tested where appropriate, intersectional disaggregation is conducted where relevant, and small sub-groups are handled transparently.
- Reporting Disaggregation: Whether disaggregated data is reported in main text and tables (not buried in annex), visualizations show sub-group differences clearly, patterns are described rather than only shown, and any inability to disaggregate is stated as a limitation.
- Use of Disaggregated Data: Whether findings reference disaggregated patterns, recommendations respond to disaggregated findings, decisions reference disaggregated evidence, and equity gaps surfaced by disaggregation are addressed in next steps.
Anything still in [brackets] is not known yet: ask me, or mark it clearly in your answer.