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Keyword

treatment effect estimation

Description: Treatment effect estimation is the statistical process of estimating causal effects of interventions or treatments on outcomes, used in causal inference and machine learning.
OpenAlex ID: keywords/treatment-effect-estimation
Quantifying heterogeneity in a meta‐analysis
2002 · Julian P. T. Higgins, Simon G. Thompson · Statistics in Medicine · 36,569
The central role of the propensity score in observational studies for causal effects
1983 · PAUL R. ROSENBAUM, DONALD B. RUBIN · Biometrika · 30,962
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Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity‐score matched samples
2009 · Peter C. Austin · Statistics in Medicine · 6,691
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Entropy Balancing for Causal Effects: A Multivariate Reweighting Method to Produce Balanced Samples in Observational Studies
2011 · Jens Hainmueller · Political Analysis · 5,951
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Propensity score methods for bias reduction in the comparison of a treatment to a non-randomized control group
1998 · Ralph B. D’Agostino · Statistics in Medicine · 5,326
Two-Way Fixed Effects Estimators with Heterogeneous Treatment Effects
2020 · Clément de Chaisemartin, Xavier D’Haultfœuille · American Economic Review · 4,962
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Propensity Score-Matching Methods for Nonexperimental Causal Studies
2002 · Rajeev H. Dehejia, Sadek Wahba · The Review of Economics and Statistics · 4,846
What's the Relative Risk?
1998 · Jun Zhang, Kai F. Yu · JAMA · 4,121
Optimal caliper widths for propensity‐score matching when estimating differences in means and differences in proportions in observational studies
2010 · Peter C. Austin · Pharmaceutical Statistics · 3,919
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Causal Inference without Balance Checking: Coarsened Exact Matching
2011 · Stefano M. Iacus, Gary King, et al. · Political Analysis · 3,532
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The Central Role of the Propensity Score in Observational Studies for Causal Effects
1983 · Paul R. Rosenbaum, Donald B. Rubin · Biometrika · 3,262
Reducing Bias in Observational Studies Using Subclassification on the Propensity Score
1984 · Paul R. Rosenbaum, Donald B. Rubin · Journal of the American Statistical Association · 3,194
Reducing Bias in Observational Studies Using Subclassification on the Propensity Score
1984 · Paul R. Rosenbaum, Donald B. Rubin · Journal of the American Statistical Association · 3,074
Evaluating non-randomised intervention studies
2003 · J Deeks, J Dinnes, et al. · Health Technology Assessment · 2,890
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Estimating Causal Effects from Large Data Sets Using Propensity Scores
1997 · Donald B. Rubin · Annals of Internal Medicine · 2,877
Combining effect size estimates in meta-analysis with repeated measures and independent-groups designs.
2002 · Scott B. Morris, Richard P. DeShon · Psychological Methods · 2,487
Causal Effects in Nonexperimental Studies: Reevaluating the Evaluation of Training Programs
1999 · Rajeev H. Dehejia, Sadek Wahba · Journal of the American Statistical Association · 2,359
Characterizing Selection Bias Using Experimental Data
1998 · James Heckman, Hidehiko Ichimura, et al. · Econometrica · 2,280
Using Propensity Scores to Help Design Observational Studies: Application to the Tobacco Litigation
2001 · Donald B. Rubin · Health Services and Outcomes Research Methodology · 2,210
PSMATCH2: Stata module to perform full Mahalanobis and propensity score matching, common support graphing, and covariate imbalance testing
2003 · Edwin Leuven, Barbara Sianesi · RePEc: Research Papers in Economics · 2,176
Statistical Methods for Examining Heterogeneity and Combining Results from Several Studies in Meta‐Analysis
2001 · Jonathan J Deeks, Douglas G Altman, et al. · 2,139
Analysing controlled trials with baseline and follow up measurements
2001 · Andrew J Vickers, Douglas G Altman · BMJ · 2,088
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Intention-to-treat concept: A review
2011 · SandeepK Gupta · Perspectives in Clinical Research · 1,915
Propensity Score Analysis: Statistical Methods and Applications
2009 · Shenyang Guo, Mark W. Fräser · 1,809
Systematic Reviews: Rationale for systematic reviews
1994 · C D Mulrow · BMJ · 1,676
Works count: 12,280
Citation count: 363,500
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