The following pages link to (Q4494193):
Displaying 50 items.
- Structural nested models and G-estimation: the partially realized promise (Q252829) (← links)
- Estimating structural mean models with multiple instrumental variables using the generalised method of moments (Q254415) (← links)
- Identification, estimation and approximation of risk under interventions that depend on the natural value of treatment using observational data (Q306793) (← links)
- A method for increasing the robustness of multiple imputation (Q434934) (← links)
- On instrumental variables estimation of causal odds ratios (Q449850) (← links)
- Heterogeneous indirect effects for multiple mediators using interventional effect models (Q829924) (← links)
- Nonparametric causal effects based on marginal structural models (Q861206) (← links)
- Identification, inference and sensitivity analysis for causal mediation effects (Q903314) (← links)
- A semiparametric model selection criterion with applications to the marginal structural model (Q959174) (← links)
- Non-parametric inference for the effect of a treatment on survival times with application in the health and social sciences (Q963906) (← links)
- Semiparametric log-linear regression for longitudinal measurements subject to outcome-depen\-dent follow-up (Q1031757) (← links)
- Is regression adjustment supported by the Neyman model for causal inference? (Q1036725) (← links)
- Choice as an alternative to control in observational studies. (With comments and a rejoinder). (Q1431170) (← links)
- Why prefer double robust estimators in causal inference? (Q1765677) (← links)
- General theory for interactions in sufficient cause models with dichotomous exposures (Q1940768) (← links)
- Revisiting g-estimation of the effect of a time-varying exposure subject to time-varying confounding (Q2001884) (← links)
- Evaluating the impact of a HIV low-risk express care task-shifting program: a case study of the targeted learning roadmap (Q2001893) (← links)
- Posterior predictive treatment assignment methods for causal inference in the context of time-varying treatments (Q2059304) (← links)
- Causal inference for the effect of mobility on Covid-19 deaths (Q2080760) (← links)
- Continuous-time targeted minimum loss-based estimation of intervention-specific mean outcomes (Q2105179) (← links)
- Linear mixed models with endogenous covariates: modeling sequential treatment effects with application to a mobile health study (Q2218059) (← links)
- Identification in nonparametric models for dynamic treatment effects (Q2236887) (← links)
- Covariate balancing functional propensity score for functional treatments in cross-sectional observational studies (Q2242173) (← links)
- Evaluating epoetin dosing strategies using observational longitudinal data (Q2258584) (← links)
- A semiparametric modeling approach using Bayesian additive regression trees with an application to evaluate heterogeneous treatment effects (Q2281248) (← links)
- Optimal restricted estimation for more efficient longitudinal causal inference (Q2343651) (← links)
- Data-adaptive estimation of the treatment-specific mean (Q2370469) (← links)
- Causal inference in longitudinal studies with history-restricted marginal structural models (Q2426797) (← links)
- Causal inference for continuous-time processes when covariates are observed only at discrete times (Q2429926) (← links)
- Double robust estimation in longitudinal marginal structural models (Q2581663) (← links)
- Structural regression model for causal inference under strongly ignorable treatment assignment (Q2720090) (← links)
- Estimating treatment effect in a proportional hazards model in randomized clinical trials with all-or-nothing compliance (Q2827183) (← links)
- Comparison of Approaches to Weight Truncation for Marginal Structural Cox Models (Q2974503) (← links)
- Confounding adjustment methods for multi-level treatment comparisons under lack of positivity and unknown model specification (Q5093035) (← links)
- Risk Factor Adjustment in Marginal Structural Model Estimation of Optimal Treatment Regimes (Q5123250) (← links)
- Data‐adaptive longitudinal model selection in causal inference with collaborative targeted minimum loss‐based estimation (Q5128783) (← links)
- (Q5148951) (← links)
- Downstream Effects of Upstream Causes (Q5208051) (← links)
- Robust Alternatives to ANCOVA for Estimating the Treatment Effect via a Randomized Comparative Study (Q5208089) (← links)
- Discussion of “Penalized Spline of Propensity Methods for Treatment Comparison” by Zhou, Elliott, and Little (Q5229886) (← links)
- Nonparametric Causal Effects Based on Incremental Propensity Score Interventions (Q5231493) (← links)
- Inverse Probability Weighted Estimation of Risk Under Representative Interventions in Observational Studies (Q5231520) (← links)
- Causal effect models for realistic individualized treatment and intention to treat rules (Q5442947) (← links)
- Efficient Estimation of Optimal Regimes Under a No Direct Effect Assumption (Q5857144) (← links)
- Nonparametric Tests of the Causal Null With Nondiscrete Exposures (Q5881156) (← links)
- Joint calibrated estimation of inverse probability of treatment and censoring weights for marginal structural models (Q6055533) (← links)
- Semiparametric estimation of structural nested mean models with irregularly spaced longitudinal observations (Q6055622) (← links)
- Structural Cumulative Survival Models for Estimation of Treatment Effects Accounting for Treatment Switching in Randomized Experiments (Q6055730) (← links)
- Causal inference: Critical developments, past and future (Q6059423) (← links)
- Coherent Modeling of Longitudinal Causal Effects on Binary Outcomes (Q6079765) (← links)
