Causal inference and trial emulation for ecological and/or environmental observational data
Not stated
- Funding
- Competition Funded PhD Project (Students Worldwide)
- Application deadline
- Year-round applications
About the project
About the Project Conducting formal causal inference for ecological and/or environmental data is challenging due to the complex observational processes that are usually involved. The propensity score method allows the estimation of causal effects in non-experimental studies, however this is dependent on constructing emulated experiments to ensure independence between the observation process and treatment allocation. This PhD will develop and apply novel methodology in causal inference and causal discovery for ecological and/or environmental observational studies, for example changes in spatio-temporal distribution and movement patterns driven by environmental disturbance and impact assessment studies.
Research areas
AppliedStatisticsDataAnalysisEcologyEnvironmentalBiologyStatisticsCausalinferenceandtrialemulationforecologicaland/orenvironmentalobservationaldata