Pages that link to "Item:Q1012712"

The following pages link to Applying quantitative bias analysis to epidemiologic data (Q1012712):

Displaying 11 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)
• When is a sensitivity parameter exactly that? (Q667684) (← links)
• Comment: The need for syncretism in applied statistics (Q903284) (← links)
• The magnitude and direction of collider bias for binary variables (Q2192289) (← links)
• Outcome-wide longitudinal designs for causal inference: a new template for empirical studies (Q2218075) (← links)
• Rejoinder: The future of outcome-wide studies (Q2218082) (← links)
• Bayesian estimation of logistic regression with misclassified covariates and response (Q5036440) (← links)
• Monte Carlo sensitivity analysis for unmeasured confounding in dynamic treatment regimes (Q6563659) (← links)
• Robust Bayesian sensitivity analysis for case-control studies with uncertain exposure misclassification probabilities (Q6593505) (← links)
• Causal inference with noisy data: bias analysis and estimation approaches to simultaneously addressing missingness and misclassification in binary outcomes (Q6627315) (← links)
• A robust Bayesian bias-adjusted random effects model for consideration of uncertainty about bias terms in evidence synthesis (Q6628639) (← links)