Model‐free causal inference of binary experimental data
نویسندگان
چکیده
منابع مشابه
Causal Inference for Binary Data with Interference
Joseph Rigdon: Causal Inference for Binary Data with Interference (Under the direction of Michael Hudgens) Developing methods to quantify the effects of interventions to prevent infectious diseases in the presence of interference is the overall objective of this research. Interference is present when an individual’s outcome is affected by the treatment of any other individuals under study. Firs...
متن کاملCausal inference with observational data
Identifying the causal impact of some variables X on y is difficult in the best of circumstances, but faces seemingly insurmountable problems in observational data, where X is not manipulable by the researcher and cannot be randomly assigned. Nevertheless, estimating such an impact or “treatment effect” is the goal of much research, even much research that carefully states all findings in terms...
متن کاملCausal Inference with Panel Data
For nearly half a century, the fundamental problem for statistical analysis in the social sciences has been how to make causal inferences from nonexperimental data (Blalock 1961). For nearly as long, there has been a widespread consensus that the best kind of nonexperimental data for making causal inferences is longitudinal data. Unfortunately, there has not been nearly as much consensus on the...
متن کاملCausal Inference in Observational Data
Our aging population increasingly suffers from multiple chronic diseases simultaneously, necessitating the comprehensive treatment of these conditions. Finding the optimal set of drugs and interventions for a combinatorial set of diseases is a combinatorial pattern exploration problem. Association rule mining is a popular tool for such problems, but the requirement of health care for finding ca...
متن کاملCausal Inference on Data Containing Deterministic Relations
Data containing deterministic relations cannot be handled by current constraint-based causal learning algorithms; they entail conditional independencies that cannot be represented by a faithful graph. Violation of the faithfulness property is characterized by an information equivalence of two sets of variables with respect to a reference variable. The conditional independencies do not provide i...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Scandinavian Journal of Statistics
سال: 2018
ISSN: 0303-6898,1467-9469
DOI: 10.1111/sjos.12343