Journal ArticleDOI
Statistics and causal inference
TLDR
In this article, a statistical model for causal inference is used to critique the discussions of other writers on causation and causal inference, including selected philosophers, medical researchers, statisticians, econometricians, and proponents of causal modelling.Abstract:
Problems involving causal inference have dogged at the heels of Statistics since its earliest days. Correlation does not imply causation and yet causal conclusions drawn from a carefully designed experiment are often valid. What can a statistical model say about causation? This question is addressed by using a particular model for causal inference (Rubin, 1974; Holland and Rubin, 1983) to critique the discussions of other writers on causation and causal inference. These include selected philosophers, medical researchers, statisticians, econometricians, and proponents of causal modelling.read more
Citations
More filters
Book
Causation, prediction, and search
TL;DR: The authors axiomatize the connection between causal structure and probabilistic independence, explore several varieties of causal indistinguishability, formulate a theory of manipulation, and develop asymptotically reliable procedures for searching over equivalence classes of causal models.
Book
Counterfactuals and Causal Inference: Methods and Principles for Social Research
TL;DR: In this article, the authors proposed a method to estimate causal effects by conditioning on observed variables to block backdoor paths in observational social science research, but the method is limited to the case of causal exposure and identification criteria for conditioning estimators.
Journal ArticleDOI
How Do Risk Factors Work Together? Mediators, Moderators, and Independent, Overlapping, and Proxy Risk Factors
TL;DR: Classifying putative risk factors into these qualitatively different types can help identify high-risk individuals in need of preventive interventions and can help inform the content of such interventions.
Journal ArticleDOI
The theoretical status of latent variables
TL;DR: It is argued that a consistent interpretation of such models requires a realist ontology for latent variables, and a typology of constructs is proposed on the basis of this analysis.
Journal ArticleDOI
Propensity score estimation with boosted regression for evaluating causal effects in observational studies.
TL;DR: Propensity score weights estimated using boosting eliminate most pretreatment group differences and substantially alter the apparent relative effects of adolescent substance abuse treatment.
References
More filters
Journal ArticleDOI
The central role of the propensity score in observational studies for causal effects
TL;DR: The authors discusses the central role of propensity scores and balancing scores in the analysis of observational studies and shows that adjustment for the scalar propensity score is sufficient to remove bias due to all observed covariates.
Journal ArticleDOI
Investigating Causal Relations by Econometric Models and Cross-Spectral Methods
TL;DR: In this article, the cross spectrum between two variables can be decomposed into two parts, each relating to a single causal arm of a feedback situation, and measures of causal lag and causal strength can then be constructed.
Book
A Treatise of Human Nature
TL;DR: Hume's early years and education is described in a treatise of human nature as discussed by the authors. But it is not a complete account of the early years of his life and education.
Journal ArticleDOI
Estimating causal effects of treatments in randomized and nonrandomized studies.
TL;DR: A discussion of matching, randomization, random sampling, and other methods of controlling extraneous variation is presented in this paper, where the objective is to specify the benefits of randomization in estimating causal effects of treatments.
Journal ArticleDOI
The environment and disease: association or causation?
TL;DR: The criteria outlined in "The Environment and Disease: Association or Causation?" help identify the causes of many diseases, including cancers of the reproductive system.