Pages that link to "Item:Q5190584"
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The following pages link to Sensitivity Analysis of Unmeasured Confounding for the Causal Risk Ratio by Applying Marginal Structural Models (Q5190584):
Displaying 16 items.
- A flexible sensitivity analysis approach for unmeasured confounding with multiple treatments and a binary outcome with application to SEER-Medicare lung cancer data (Q124494) (← links)
- Sensitivity analysis for unmeasured confounding in a marginal structural Cox proportional hazards model (Q841066) (← links)
- Alternative sensitivity analyses for regression estimates of treatment effects to unobserved confounding in binary and survival data (Q2082465) (← links)
- Regression analysis of unmeasured confounding (Q2197498) (← links)
- Bayesian sensitivity analysis to unmeasured confounding for misclassified data (Q2234731) (← links)
- Simple Formulae for Evaluating the Potential Impact of Confounding Bias (Q2892630) (← links)
- Monte-Carlo Sensitivity Analysis for Controlled Direct Effects Using Marginal Structural Models in the Presence of Confounded Mediators (Q2920002) (← links)
- Generalized Cornfield conditions for the risk difference (Q2934774) (← links)
- Double Inverse-Weighted Estimation of Cumulative Treatment Effects Under Nonproportional Hazards and Dependent Censoring (Q3008854) (← links)
- Simplified Bayesian Sensitivity Analysis for Mismeasured and Unobserved Confounders (Q3076042) (← links)
- Sensitivity analysis for causal inference using inverse probability weighting (Q3100766) (← links)
- Sensitivity Analysis: Distributional Assumptions and Confounding Assumptions (Q3506517) (← links)
- An Approach for Estimating Causal Effects in Randomized Trials with Noncompliance (Q3585306) (← links)
- Estimating a Marginal Causal Odds Ratio Subject to Confounding (Q3622049) (← links)
- Sensitivity Analysis for Unmeasured Confounding in Coarse Structural Nested Mean Models (Q4558439) (← links)
- Assessing the Sensitivity of Regression Results to Unmeasured Confounders in Observational Studies (Q4666038) (← links)
