Results 11 to 20 of about 117 (76)
Conditional average treatment effect estimation with marginally constrained models [PDF]
Journal of Causal Inference, 2023 Treatment effect estimates are often available from randomized controlled trials as a single average treatment effect for a certain patient population.
van Amsterdam Wouter A. C. +1 more
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Quantifying the quality of configurational causal models [PDF]
Journal of Causal InferenceThere is a growing number of studies benchmarking the performance of configurational comparative methods (CCMs) of causal data analysis. A core benchmark criterion used in these studies is a dichotomous (i.e., non-quantitative) correctness criterion ...
Baumgartner Michael, Falk Christoph
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Journal of Causal Inference, 2023 Inferring the effect of interventions within complex systems is a fundamental problem of statistics. A widely studied approach uses structural causal models that postulate noisy functional relations among a set of interacting variables.
Strieder David, Drton Mathias
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Beyond conditional averages: Estimating the individual causal effect distribution [PDF]
Journal of Causal InferenceIn recent years, the field of causal inference from observational data has emerged rapidly. The literature has focused on (conditional) average causal effect estimation.
Post Richard A. J. +1 more
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Simple yet sharp sensitivity analysis for unmeasured confounding
Journal of Causal Inference, 2022 We present a method for assessing the sensitivity of the true causal effect to unmeasured confounding. The method requires the analyst to set two intuitive parameters. Otherwise, the method is assumption free. The method returns an interval that contains
Peña Jose M.
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A new three-step method for using inverse propensity weighting with latent class analysis [PDF]
, 2022 Bias-adjusted three-step latent class analysis (LCA) is widely popular to relate covariates to class membership. However, if the causal effect of a treatment on class membership is of interest and only observational data is available, causal inference ...
Clouth, F. J. +3 more
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Estimating marginal treatment effects under unobserved group heterogeneity
Journal of Causal Inference, 2022 This article studies the treatment effect models in which individuals are classified into unobserved groups based on heterogeneous treatment rules. By using a finite mixture approach, we propose a marginal treatment effect (MTE) framework in which the ...
Hoshino Tadao, Yanagi Takahide
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Robust variance estimation and inference for causal effect estimation
Journal of Causal Inference, 2023 We present two novel approaches to variance estimation of semi-parametric efficient point estimators of the treatment-specific mean: (i) a robust approach that directly targets the variance of the influence function (IF) as a counterfactual mean outcome ...
Tran Linh +3 more
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Examination of the 1970 National Bureau of Standards Underground Corrosion Test Welded Stainless STeel Coupons from Site D [PDF]
, 2008 A 1970 study initiated by the National Bureau of Standards (NBS), now known as the National Institute of Standards and Technology (NIST), buried over 6000 corrosion coupons or specimens of stainless steel Types 201, 202, 301, 304, 316, 409, 410, 430, and
Flitton, M. K. Adler +3 more
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Attributable fraction and related measures: Conceptual relations in the counterfactual framework
Journal of Causal Inference, 2023 The attributable fraction (population) has attracted much attention from a theoretical perspective and has been used extensively to assess the impact of potential health interventions. However, despite its extensive use, there is much confusion about its
Suzuki Etsuji, Yamamoto Eiji
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