Check the results are consistent with causal contribution
One of the tasks involved in understanding causes is to check whether the observed results are consistent with a cause-effect relationship between the intervention and the observed impacts.
Some of the methods for this task involve an analysis of existing data and some involve additional data collection. It is often appropriate to use several methods in a single evaluation. Most impact evaluations should include some methods that address this task.
Methods
Gathering additional data
Analysis
Approaches
These approaches combine some of the above options together with ruling out possible alternative explanations.
Expand to view all resources related to 'Check the results are consistent with causal contribution'
Ressource
- Better late than never: Workforce supply implications of later entry into nursing
- Broadening the range of designs and methods for impact evaluations
- Making rigorous causal claims in a real-life context: Has research contributed to sustainable forest management?
- Monitoring and evaluation for thinking and working politically
- Overview: Strategies for causal attribution
- Process tracing and contribution analysis: A combined approach to generative causal inference for impact evaluation
- Présentation des stratégies d'attribution causale
- Set-theoretic methods for the social sciences: A guide to qualitative comparative analysis
- Sinopsis: estrategias de atribución causal
'Check the results are consistent with causal contribution' is referenced in:
Approach
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Rahmenkonzept/Anleitung
- Communication for Development (C4D) :
- Communication for Development (C4D) :
- Rainbow Framework :