Methods for causal inference from gene perturbation experiments and validation

Methods for causal inference from gene perturbation experiments and validation.

Inferring causal effects from observational and interventional data is a highly desirable but ambitious goal. Many of the computational and statistical methods are plagued by fundamental identifiability issues, instability, and unreliable performance, especially for large-scale systems with many measured variables. We present software and provide some validation of a recently developed methodol...

Causal inference from indirect experiments

An indirect experiment is a study in which randomized control is replaced by randomized encouragement, that is, subjects are encouraged, rather than forced, to receive a given treatment program. The purpose of this paper is to bring to the attention of experimental researchers simple mathematical results that enable us to assess, from indirect experiments, the strength with which causal influen...

Matching Methods for Causal Inference

Complete Identi cation Methods for Causal Inference

of the Dissertation Complete Identification Methods for Causal Inference

Causal Inference by Surrogate Experiments: z-Identifiability

We address the problem of estimating the effect of intervening on a set of variables X from experiments on a different set, Z, that is more accessible to manipulation. This problem, which we call z-identifiability, reduces to ordinary identifiability when Z = ∅ and, like the latter, can be given syntactic characterization using the do-calculus [Pearl, 1995; 2000]. We provide a graphical necessa...