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Journal of Causal Inference
中科院4区 JCR:Q2 SCIE SSCI PubMed JST
Journal of Causal Inference publishes papers on theoretical and applied causal research across the range of academic disciplines that use quantitative tools to study causality. The past two decades have seen causal inference emerge as a unified field with a solid theoretical foundation, useful in many of the empirical and behavioral sciences. Journal of Causal Inference aims to provide a common venue for researchers working on causal inference in biostatistics and epidemiology, economics, political science and public policy, cognitive science and formal logic, and any field that aims to understand causality. The journal serves as a forum for this growing community to develop a shared language and study the commonalities and distinct strengths of their various disciplines' methods for causal analysis.
- 主办单位： DE GRUYTER POLAND SP Z O O
- 出版地区： WARSAW
- 出版周期： 连续出版
- 别名： J CAUSAL INFERENCE;J. Causal Inference;JOURNAL OF CAUSAL INFERENCE
- 国际标准连续出版物号/电子版： ISSN 2193-3677 / EISSN 2193-3685
- 创刊时间： 2013年
热门主题：
Causal InferenceAverage Treatment EffectPropensity ScoreTreatment EffectCausal EffectUnmeasured ConfoundingSensitivity AnalysisTreatment EffectsTargeted Maximum Likelihood EstimationRandomized ExperimentsAverage Causal EffectAverage Treatment EffectsCausal ModelsStructural Causal ModelsCovariate BalanceInverse Probability WeightingEffect EstimationStatistical CausalityRobust EstimationTargeted Learning
期刊信息
- 主办单位：DE GRUYTER POLAND SP Z O O
- 地 址： WARSAW
期刊简介
Journal of Causal Inference publishes papers on theoretical and applied causal research across the range of academic disciplines that use quantitative tools to study causality. The past two decades have seen causal inference emerge as a unified field with a solid theoretical foundation, useful in many of the empirical and behavioral sciences. Journal of Causal Inference aims to provide a common venue for researchers working on causal inference in biostatistics and epidemiology, economics, political science and public policy, cognitive science and formal logic, and any field that aims to understand causality. The journal serves as a forum for this growing community to develop a shared language and study the commonalities and distinct strengths of their various disciplines' methods for causal analysis.