相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。On the Nondifferential Misclassification of a Binary Confounder
Elizabeth L. Ogburn et al.
EPIDEMIOLOGY (2012)
Berkson's Bias, Selection Bias, and Missing Data
Daniel Westreich
EPIDEMIOLOGY (2012)
Invited Commentary: Understanding Bias Amplification
Judea Pearl
AMERICAN JOURNAL OF EPIDEMIOLOGY (2011)
Weight Trimming and Propensity Score Weighting
Brian K. Lee et al.
PLOS ONE (2011)
CAUSAL DIAGRAMS FOR TREATMENT EFFECT ESTIMATION WITH APPLICATION TO EFFICIENT COVARIATE SELECTION
Halbert White et al.
REVIEW OF ECONOMICS AND STATISTICS (2011)
On quantifying the magnitude of confounding
Holly Janes et al.
BIOSTATISTICS (2010)
On the Consistency Rule in Causal Inference Axiom, Definition, Assumption, or Theorem?
Judea Pearl
EPIDEMIOLOGY (2010)
Selective Ignorability Assumptions in Causal Inference
Marshall M. Joffe et al.
INTERNATIONAL JOURNAL OF BIOSTATISTICS (2010)
An Introduction to Causal Inference
Judea Pearl
INTERNATIONAL JOURNAL OF BIOSTATISTICS (2010)
Signed directed acyclic graphs for causal inference
Tyler J. VanderWeele et al.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY (2010)
Graphical Models for Inference Under Outcome-Dependent Sampling
Vanessa Didelez et al.
STATISTICAL SCIENCE (2010)
Adjusting for selection bias in retrospective, case-control studies
Sara Geneletti et al.
BIOSTATISTICS (2009)
Concerning the Consistency Assumption in Causal Inference
Tyler J. VanderWeele
EPIDEMIOLOGY (2009)
On the Relative Nature of Overadjustment and Unnecessary Adjustment
Tyler J. VanderWeele
EPIDEMIOLOGY (2009)
The Consistency Statement in Causal Inference A Definition or an Assumption?
Stephen R. Cole et al.
EPIDEMIOLOGY (2009)
Overadjustment Bias and Unnecessary Adjustment in Epidemiologic Studies
Enrique F. Schisterman et al.
EPIDEMIOLOGY (2009)
Should observational studies be designed to allow lack of balance in covariate distributions across treatment groups? REPLY
Donald B. Rubin
STATISTICS IN MEDICINE (2009)
Causal directed acyclic graphs and the direction of unmeasured confounding bias
Tyler J. VanderWeele et al.
EPIDEMIOLOGY (2008)
Demystifying double robustness: A comparison of alternative strategies for estimating a population mean from incomplete data
Joseph D. Y. Kang et al.
STATISTICAL SCIENCE (2007)
A comparison of the ability of different propensity score models to balance measured variables between treated and untreated subjects: a Monte Carlo study
Peter C. Austin et al.
STATISTICS IN MEDICINE (2007)
Instruments for causal inference -: An epidemiologist's dream?
MA Hernán et al.
EPIDEMIOLOGY (2006)
Variable selection for propensity score models
M. Alan Brookhart et al.
AMERICAN JOURNAL OF EPIDEMIOLOGY (2006)
A structural approach to selection bias
MA Hernán et al.
EPIDEMIOLOGY (2004)
Propensity score estimation with boosted regression for evaluating causal effects in observational studies
DF McCaffrey et al.
PSYCHOLOGICAL METHODS (2004)
Marginal structural models as a tool for standardization
T Sato et al.
EPIDEMIOLOGY (2003)
Fallibility in estimating direct effects
SR Cole et al.
INTERNATIONAL JOURNAL OF EPIDEMIOLOGY (2002)
Criteria for confounders in epidemiological studies
Z Geng et al.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY (2002)
Conditions for non-confounding and collapsibility without knowledge of completely constructed causal diagrams
Z Geng et al.
SCANDINAVIAN JOURNAL OF STATISTICS (2002)
Consecutive collapsibility of odds ratios over an ordinal background variable
JH Guo et al.
JOURNAL OF MULTIVARIATE ANALYSIS (2001)
Data, design, and background knowledge in etiologic inference
JM Robins
EPIDEMIOLOGY (2001)
Marginal structural models and causal inference in epidemiology
JM Robins et al.
EPIDEMIOLOGY (2000)