What can Statistics Contribute to a Causal Understanding?
From MaRDI portal
Publication:5430605
DOI10.1111/j.1467-9469.2006.00549.xzbMath1142.62001OpenAlexW2042973431MaRDI QIDQ5430605
Publication date: 16 December 2007
Published in: Scandinavian Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1111/j.1467-9469.2006.00549.x
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Foundations and philosophical topics in statistics (62A01) Stochastic processes (60G99)
Related Items (7)
A General Dynamical Statistical model with Causal Interpretation ⋮ Causality with finite horizon of the past in continuous time ⋮ Application of multistate models in hospital epidemiology: Advances and challenges ⋮ Invariance of statistical causality under convergence ⋮ On Granger causality and the effect of interventions in time series ⋮ A general definition of influence between stochastic processes ⋮ Estimation of Direct Effects for Survival Data by using the Aalen Additive Hazards Model
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Dynamic path analysis -- a new approach to analyzing time-dependent covariates
- Dynamic modelling and causality
- Sensitivity Analysis for the Assessment of Causal Vaccine Effects on Viral Load in HIV Vaccine Trials
- A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effect
- Investigating Causal Relations by Econometric Models and Cross-spectral Methods
- Exploring complex networks
- Graphical Models for Composable Finite Markov Processes
- Composable Markov processes
- Statistical models based on counting processes
This page was built for publication: What can Statistics Contribute to a Causal Understanding?
