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Causality

Creator:   Editorial Office
Created:   1/17/2011
Contains:  61 items

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Distribution-Free Mediation Analysis for Nonlinear Models with Confounding

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Mediation Analysis With Multiple Versions of the Mediator

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Completion Potentials of Sufficient Component Causes

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Alternative Assumptions for the Identification of Direct and Indirect Effects

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Transportability and Causal Generalization

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Causal Interactions in the Proportional Hazards Model

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Differences Between Marginal Structural Models and Conventional Models in Their Exposure Effect Estimates: A Systematic Review

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Causal Mediation Analysis With Survival Data

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Direct and Indirect Effects in a Survival Context

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Compound Treatments, Transportability, and the Structural Causal Model: The Power and Simplicity of Causal Graphs

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Compound Treatments and Transportability of Causal Inference

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On the Link Between Sufficient-cause Model and Potential-outcome Model

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A Method for Detection of Residual Confounding in Time-series and Other Observational Studies

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On the Consistency Rule in Causal Inference: Axiom, Definition, Assumption, or Theorem?

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Sufficient-cause Interaction

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dagR: A Suite of R Functions for Directed Acyclic Graphs

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Bias Formulas for Sensitivity Analysis for Direct and Indirect Effects

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Negative Controls: A Tool for Detecting Confounding and Bias in Observational Studies

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DAG Program:: Identifying Minimal Sufficient Adjustment Sets

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Causal Models

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Causal Models

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Concerning the Consistency Assumption in Causal Inference

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On the Distinction Between Interaction and Effect Modification

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Mediating Various Direct-effect Approaches

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Estimating Direct Effects in Cohort and Case–Control Studies

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Bringing Causal Models Into the Mainstream

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Marginal Structural Models for the Estimation of Direct and Indirect Effects

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Interactions in Epidemiology: Relevance, Identification, and Estimation

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Sufficient Cause Interactions and Statistical Interactions

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The Consistency Statement in Causal Inference: A Definition or an Assumption?

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Causal Directed Acyclic Graphs and the Direction of Unmeasured Confounding Bias

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Four Types of Effect Modification: A Classification Based on Directed Acyclic Graphs

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Properties of 2 Counterfactual Effect Definitions of a Point Exposure

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The Identification of Synergism in the Sufficient-Component-Cause Framework

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Instruments for Causal Inference: An Epidemiologist's Dream?

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Estimation of Direct Causal Effects

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Bounding Causal Effects Under Uncontrolled Confounding Using Counterfactuals

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A Structural Approach to Selection Bias

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Marginal Structural Models as a Tool for Standardization

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Quantifying Biases in Causal Models: Classical Confounding vs Collider-Stratification Bias

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Data, Design, and Background Knowledge in Etiologic Inference

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A Psychometric Experiment in Causal Inference to Estimate Evidential Weights Used by Epidemiologists

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Causal Values

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Marginal Structural Models to Estimate the Causal Effect of Zidovudine on the Survival of HIV-Positive Men

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Marginal Structural Models and Causal Inference in Epidemiology

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Causal Diagrams for Epidemiologic Research.

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Probability Logic and Probabilistic Induction.

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Reproductive Factors, Oral Contraceptive Use, and Risk of Colorectal Cancer.

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Imputation for Exposure Histories with Gaps, under an Excess Relative Risk Model.

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Causal Inference in Infectious Diseases.

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ERRATUM.

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Causal Inference.

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Measures of Effect Based on the Sufficient Causes Model. 2. Risks and Rates of Disease Associated with a Single Preventive Agent.

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Measures of Effect Based on the Sufficient Causes Model.

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Measures of Effect Based on the Sufficient Causes Model. 1. Risks and Rates of Disease Associated with a Single Causative Agent.

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G-Estimation of the Effect of Prophylaxis Therapy for Pneumocystis carinii Pneumonia on the Survival of AIDS Patients.

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Time-Related Confounders and Intermediate Variables.

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Identifiability and Exchangeability for Direct and Indirect Effects.

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On the Origin of Hill's Causal Criteria.

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Randomization, Statistics, and Causal Inference.

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White Swans, Black Ravens, and Lame Ducks: Necessary and Sufficient Causes in Epidemiology.

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