A Python package for causal inference using Synthetic Controls
A PyTorch implementation of the "robust" synthetic control model
Claude skill and Claude Code plugin for designing, prioritising and quality-assuring evaluation questions and evaluation matrices for development and humanitarian programmes. Applies OECD-DAC and UNEG standards and adapts them to EU, World Bank, UNICEF, FCDO and other donor frameworks.
AI-assisted program evaluation engine for small healthcare orgs: naive vs adjusted estimates side by side, every correction documented, every limitation stated. Statistics decide; AI assists.
Public-sector analytics capstone using 239,110 NH assessment records to benchmark Manchester outcomes and identify support priorities.
Reusable governance and delivery toolkit for applied research and evaluation, including charters, work plans, risk controls, and stage gates.
Empirical L&D decision-threshold study of randomized NSW training evidence with bootstrap and permutation robustness.
UMAPS data project that cleans, standardizes, and visualizes alumni and participation records to support program reporting, strategic planning, and institutional memory.
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