Cited by 1,150Advanced Causal Inference TechniquesStatistical Methods in EpidemiologyOptimal Experimental Design Methods

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Design of Observational Studies

Rosenbaum, Paul R.·2010·Springer Series in Statistics

DOI 10.1007/978-1-4419-1213-8

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The Bias Due to Incomplete Matching
Rosenbaum, P. R., & Rubin, D. B. (1985) · Biometrics · doi:10.2307/2530647 · Cited by 532
Self-citation
Does Cardiac Transplantation Prolong Life?
Gail, M. H. (1972) · Annals of Internal Medicine · doi:10.7326/0003-4819-76-5-815 · Cited by 124
Causal Inference in Randomized Experiments
Rosenbaum, P. R. (2009) · Springer series in statistics · doi:10.1007/978-1-4419-1213-8_2 · Cited by 10
Self-citation
Competing Theories Structure Design
Rosenbaum, P. R. (2009) · Springer series in statistics · doi:10.1007/978-1-4419-1213-8_4 · Cited by 4
Self-citation
Two Simple Models for Observational Studies
Rosenbaum, P. R. (2009) · Springer series in statistics · doi:10.1007/978-1-4419-1213-8_3 · Cited by 3
Self-citation
Uncommon but Dramatic Responses to Treatment
Rosenbaum, P. R. (2009) · Springer series in statistics · doi:10.1007/978-1-4419-1213-8_16 · Cited by 2
Self-citation
Multiple Control Groups
Rosenbaum, P. R. (1995) · Springer series in statistics · doi:10.1007/978-1-4757-2443-1_7 · Cited by 2
Self-citation
Causal Inference in Randomized Experiments
Rosenbaum, P. R. (2021) · Chapman & Hall/CRC eBooks · doi:10.1201/9781003039648-ch1 · Cited by 2
Self-citation
Internal and External Validity
(2020) · doi:10.4135/9781529692730 · Cited by 2
Solutions to Common Problems
(2008) · Apress eBooks · doi:10.1007/978-1-4302-0523-4_18 · Cited by 1

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“Besides, the difference-in-means estimator is simpler and provides more transparent analysis for the treatment effects (Cox, 2007; Freedman, 2008; Rosenbaum, 2010).”
Method
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Kelly, R. (2015) · The Gerontologist · doi:10.1093/geront/gnv145 · Cited by 13
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“10, a commonly recommended threshold (Rosenbaum 2010).”
Blocking for Sequential Political Experiments
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Association between use of pre-hospital ECG and 30-day mortality: A large cohort study of patients experiencing chest pain
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Metformin therapy and postoperative atrial fibrillation in diabetic patients after cardiac surgery
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Increasing Power for Observational Studies of Aberrant Response: An Adaptive Approach
Heng, S., Kang, H., Small, D. S., & Fogarty, C. B. (2021) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/rssb.12424 · Cited by 13
Stratified Restricted Mean Survival Time Model for Marginal Causal Effect in Observational Survival Data
Ni, A., Lin, Z., & Lü, B. (2021) · Annals of Epidemiology · doi:10.1016/j.annepidem.2021.09.016 · Cited by 12
Toward tailored care for families with multiple problems: A quasi‐experimental study on effective elements of care
Visscher, L., Reijneveld, S. A., Knot‐Dickscheit, J., van Yperen, T. A., Scholte, R. H. J., Delsing, M. J. M. H., Evenboer, E., & Jansen, D. E. M. C. (2021) · Family Process · doi:10.1111/famp.12745 · Cited by 12
Matching design for augmenting the control arm of a randomized controlled trial using real-world data
Liu, Y., Lü, B., Foster, R., Zhang, Y., Zhong, Z. J., Chen, M., & Sun, P. (2022) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543406.2021.2011900 · Cited by 12
“So robust/rank-based Mahalanobis distance was proposed as an alternative measure by replacing the covariates with their ranks and using an adjusted covariance matrix (Rosenbaum 2010).”
BackgroundMethodInfluential
Impact of the matching algorithm on the treatment effect estimate: A neutral comparison study
Heinz, P., Wendel‐Garcia, P. D., & Held, U. (2022) · Zurich Open Repository and Archive (University of Zurich) · doi:10.5167/uzh-223417 · Cited by 12
Using Scheffé projections for multiple outcomes in an observational study of smoking and periodontal disease
Rosenbaum, P. R. (2016) · The Annals of Applied Statistics · doi:10.1214/16-aoas942 · Cited by 12
Self-citation
The association between maternal employment and child survival in India, 1998–99 and 2005–06
Saabneh, A. (2016) · Asian Population Studies · doi:10.1080/17441730.2016.1239412 · Cited by 12
Impacts of the Brazilian innovation tax policy on the composition of private investments and on the type of innovation
Colombo, D. G. E., & da Cruz, H. N. (2018) · Revista Brasileira de Inovação · doi:10.20396/rbi.v17i2.8651500 · Cited by 12
Risk of Persistent Opioid Use following Major Surgery in Matched Samples of Patients with and without Cancer
Falcone, M., Luo, C., Chen, Y., Birtwell, D. L., Cheatle, M. D., Duan, R., Gabriel, P. E., He, L., Ko, E. M., Lenz, H., et al. (2020) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-20-0628 · Cited by 13
Robust differential abundance test in compositional data
Wang, S. (2022) · Biometrika · doi:10.1093/biomet/asac029 · Cited by 12
Affordable False Teeth: The Effects of Patient Cost Sharing on Denture Utilization and Subjective Chewing Ability
Ando, M., & Takaku, R. (2015) · The B E Journal of Economic Analysis & Policy · doi:10.1515/bejeap-2015-0194 · Cited by 12
Designing experiments informed by observational studies
Rosenman, E. T. R., & Owen, A. B. (2021) · Journal of Causal Inference · doi:10.1515/jci-2021-0010 · Cited by 13
A National Analysis of Music Coursetaking, Social-Emotional Learning, and Academic Achievement Using Propensity Scores
Shaw, B. P. (2021) · Journal of Research in Music Education · doi:10.1177/00224294211006415 · Cited by 17
“…music students, there was adequate overlap in the distributions of the propensity scores between the control and treatment groups, and the absolute standardized mean difference dx was under the desired 0.2 for all of the covariates in the matching algorithm (Haviland et al., 2007; Rosenbaum, 2010).”
BackgroundMethodInfluential
Untersuchungsdesign
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Healthcare Costs for Insured Older U.S. Adults with Hearing Loss
Simpson, A. N., Simpson, K. N., & Dubno, J. R. (2018) · Journal of the American Geriatrics Society · doi:10.1111/jgs.15425 · Cited by 12
Can $p$-values be meaningfully interpreted without random sampling?
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Mendelian Randomization Methods for Causal Inference: Estimands, Identification and Inference
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Patterns in the Sequential Treatment of Patients With Rheumatoid Arthritis Starting a Biologic or Targeted Synthetic Disease‐Modifying Antirheumatic Drug: 10‐Year Experience From a US‐Based Registry
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“As an alternative, observational data on treatment decisions and outcomes might provide opportunities to evaluate new strategies without requiring the expenses and/or prolonged duration of randomized controlled trials (6).”
Background
Diagnosing Model Performance Under Distribution Shift
Cai, T., Namkoong, H., & Yadlowsky, S. (2025) · Operations Research · doi:10.1287/opre.2023.0217 · Cited by 56
Comparative Effectiveness and Safety of a Catheterization Laboratory–Only Eptifibatide Dosing Strategy in Patients Undergoing Percutaneous Coronary Intervention
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Performance Assessment as an Application of Causal Inference
Longford, N. T. (2019) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/rssa.12529 · Cited by 11
“(2014) and Rosenbaum (2017), chapter 11), is defined by their backgrounds.”
Background
PCA Rerandomization
Zhang, H., Yin, G., & Rubin, D. B. (2023) · Canadian Journal of Statistics · doi:10.1002/cjs.11765 · Cited by 17
Testing Biased Randomization Assumptions and Quantifying Imperfect Matching and Residual Confounding in Matched Observational Studies
Chen, K., Heng, S., Long, Q., & Zhang, B. (2022) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.2022.2116447 · Cited by 11
“For instance, one way to do this is to perform a randomization inference under a biased randomization scheme using Rosenbaum bounds (Rosenbaum 2002, 2010) with the parameter set to the magnitude of the residual sensitivity value, that is, = ̃.”
BackgroundMethodInfluential
Diabetic nephropathy in a sibling and albuminuria predict early GFR decline: a prospective cohort study
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Hereditary vulnerabilities to post-operative cognitive dysfunction and dementia
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African American Turnout and African American Candidates
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Picking the lock: how universal healthcare programs influence entrepreneurial activities
Kuo, Y.-C., & Lin, J.-H. (2018) · Small Business Economics · doi:10.1007/s11187-018-0077-6 · Cited by 11
Displaced and segregated: The socio-economic status of the second generation of internally displaced Palestinians in Israel
Saabneh, A. (2018) · Population Studies · doi:10.1080/00324728.2018.1544658 · Cited by 11
“Lower postmatching values of the measure of absolute standardized difference (results not presented) also indicate a reduction in imbalance (Rosenbaum 2010, pp. 187– 90).”
BackgroundMethod
Educational attainment and environmental concern in China: An instrumental variable approach
Olivos, F., Vélez, G. F. P., Olivos‐Jara, P., & Liu, M. (2020) · Asian Journal Of Social Psychology · doi:10.1111/ajsp.12431 · Cited by 11
Make a promise: the valuation adjustment mechanism in Chinese private target acquisitions
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All Else Equal in Theory and Data (Big or Small)
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Evidence-Based Versus Junk-Based Evaluation Research
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Using Simulation to Analyze Interrupted Time Series Designs
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“We borrow from the potential outcomes viewpoint (for an overview, see Imbens and Rubin (2015) or Rosenbaum (2009)) to make the above more precise.”
Background
Treatment effect quantiles in stratified randomized experiments and matched observational studies
Su, Y., & Li, X. (2023) · Biometrika · doi:10.1093/biomet/asad030 · Cited by 10
Paleoecology grand challenge
Biondi, F. (2014) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2014.00050 · Cited by 10
Incentive‐compatible contracts in merger negotiations: The role of acquirer idiosyncratic stock return volatility
Alexakis, D., & Barbopoulos, L. G. (2019) · Financial Markets Institutions and Instruments · doi:10.1111/fmii.12124 · Cited by 10
Assessment of heterogeneous treatment effect estimation accuracy via matching
Gao, Z., Hastie, T. J., & Tibshirani, R. J. (2021) · Statistics in Medicine · doi:10.1002/sim.9010 · Cited by 13
Effects of Apprenticeship on the Short-Term Educational Outcomes of Vocational High-School Students
de Amesti, J., & Claro, S. (2021) · Journal of Research on Educational Effectiveness · doi:10.1080/19345747.2021.1917026 · Cited by 11
An introduction to propensity-score methods for reducing confounding in observational studies
Austin, P. C. (2011) · Multivariate Behavioral Research · Cited by 10
Some models and methods for the analysis of observational data
Ferreira, J. A. (2015) · Statistics Surveys · doi:10.1214/15-ss110 · Cited by 10
Comparability of Online- and Paper-Based Tests in a Statewide Assessment Program
Seo, D. G., & Jong, G. D. (2015) · Journal of Educational Computing Research · doi:10.1177/0735633114568856 · Cited by 10
Welfare Impact of Wheat Farmers Participation in the Value Chain in Tanzania
Warsanga, W. B., & Evans, E. A. (2018) · Modern Economy · doi:10.4236/me.2018.94055 · Cited by 10
HWA Expanded Scopes of Practice program evaluation: Physiotherapists in the Emergency Department sub-projec:t final report
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Reasoning About Interference between UnitsPreprint
Bowers, J., Fredrickson, M., & Panagopoulos, C. (2012) · SSRN Electronic Journal · doi:10.2139/ssrn.2115619 · Cited by 10
Improving Farm Competitiveness through Farm-Investment Support: a Propensity Score Matching ApproachPreprint
Kirchweger, S., & Kantelhardt, J. (2012) · RePEc: Research Papers in Economics · doi:10.22004/ag.econ.135791 · Cited by 10
Resolve, Reputation, and War: Cultures of Honor and Leaders' Time-in-Office
Dafoe, A. (2012) · eScholarship (California Digital Library) · Cited by 10
Factorial Survey Experiments in the Sociology of Education. Potentials, Pitfalls, Evaluation
Petzold, K. (2022) · Swiss Journal of Sociology · doi:10.2478/sjs-2022-0001 · Cited by 9
The effectiveness of vocational secondary education on entry‐level job outcomes in Japan: Safety net for low‐educated youth in a vocationally weak educational system
Ogawa, K. (2023) · Japanese Journal of Sociology · doi:10.1111/ijjs.12154 · Cited by 9
The role of climate smart agricultural practices on household income and food security: A propensity score matching approach
Tesfaye, A., Hammond, J., Radeny, M., Recha, J. W., Nigussie, A., Ambaw, G., van Wijk, M. T., Tamene, L. D., Abera, W., Demeke, G., et al. (2023) · Cogent Social Sciences · doi:10.1080/23311886.2023.2273959 · Cited by 9
“Sensitivity analysis appraises how the conclusions of a study might be altered by hidden biases of various magnitudes (Rosenbaum, 2010).”
Background
An Empirical Investigation of Manufacturers’ Operations Innovations in New Product Development Enabled by E-Commerce Platforms
Zhang, Y., Peng, X. (., Zhao, X., & Lei, Y. (2024) · Production and Operations Management · doi:10.1177/10591478231224958 · Cited by 10
A Comparison of Outcomes With Apixaban, Rivaroxaban, and Warfarin for Atrial Fibrillation and/or Venous Thromboembolism
Schaefer, J. K., Errickson, J., Kong, X., Ali, M. A., Chipalkatti, N., Haymart, B., Kaatz, S., Krol, G. D., Sood, S. L., Froehlich, J. B., et al. (2025) · JACC Advances · doi:10.1016/j.jacadv.2025.101714 · Cited by 11
Multimorbidity progression and the heterogeneous impact of healthy ageing risk factors: a multicohort study
Han, S., Chen, W., Shen, M., Shao, R., Yang, W., & Wang, C. (2025) · BMJ Public Health · doi:10.1136/bmjph-2024-002474 · Cited by 10
Split-door criterion: Identification of causal effects through auxiliary outcomes
Sharma, A. K., Hofman, J. M., & Watts, D. J. (2018) · The Annals of Applied Statistics · doi:10.1214/18-aoas1179 · Cited by 9
“Correspondingly, sensitivity analyses designed for back-door-based methods [Harding, 2009; Rosenbaum, 2010; VanderWeele and Arah, 2011; Carnegie, Harada and Hill, 2016] can be readily adapted to analyzing split-door instances.”
Method
Enhancing (Publications on) Data Quality: Deeper Data Minding and Fuller Data Confession
Meng, X. (2021) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/rssa.12762 · Cited by 9
Long‐term effects of targeted prevention programmes for families with young children: A population‐based study on parenting stress and children's negative emotionality
Ulrich, S. M., Lux, U., Liel, C., & Walper, S. (2022) · Child Care Health and Development · doi:10.1111/cch.12985 · Cited by 9
The line of fifths and the co-evolution of tonal pitch-classes
Moss, F. C., Neuwirth, M., & Rohrmeier, M. (2022) · Journal of Mathematics and Music · doi:10.1080/17459737.2022.2044927 · Cited by 9
“Asitis common in observational studies (Rosenbaum 2010), caution is thus warranted when one attempts to generalize any ﬁndings derived on the basis of this data set to the entire population of polyphonic Western compositions too readily.”
Background
Coping with Externally Imposed Energy Constraints: Competitiveness and Operational Impact of China’s Top-1000 Energy-Consuming Enterprises Program
Xiao, Y., Yin, H., & Moon, J. J. (2022) · The Energy Journal · doi:10.5547/01956574.44.2.yxia · Cited by 9
A comparative study on the role of microcredit on agricultural production improvement among resource-poor rural women
Namayengo, F. M. M., van Ophem, J. A. C., & Antonides, G. (2023) · Frontiers in Sustainable Food Systems · doi:10.3389/fsufs.2023.1083660 · Cited by 9
“According to Rosenbaum (2010) τATT can be expressed as: τATT = EP(X)|D= 1 [E[Y(1)|D= 1,P(X)]−E[Y(0|D. = 0,P (X)] (2) Where P(X) is the propensity score, that is, the probability of an individual to participate in the microcredit program given the observed characteristics.”
Method
Using Differential Comparisons in Observational Studies
Rosenbaum, P. R. (2013) · CHANCE · doi:10.1080/09332480.2013.845002 · Cited by 9
Self-citation
Structured Testing of 2×2 Factorial Effects: An Analytic Plan Requiring Fewer Observations
Small, D. S., Volpp, K. G. M., & Rosenbaum, P. R. (2011) · The American Statistician · doi:10.1198/tast.2011.10130 · Cited by 9
Self-citation
Precooked developer dashboards
Ivanov, V. V., Rogers, A., Succi, G., Yi, J., & Zorin, V. (2018) · ACM/IEEE International Conference on Software Engineering: Companion Proceedings (ICSE-Companion) · doi:10.1145/3183440.3195028 · Cited by 9
“to see in dashboards with an observational study [12], (2) providing a”
GIS for empirical research design: An illustration with georeferenced point data
Kogure, K., & Takasaki, Y. (2019) · PLoS ONE · doi:10.1371/journal.pone.0212316 · Cited by 10
“In spatial contexts, this experimental approach is generally not feasible, so researchers need to rely on a quasi-experimental approach using observational data to approximate an experimental study [8].”
Method
Does Immigrant Selection Policy Matter? Labor Market Integration of Ethiopian Immigrants in Israel and the United States
Saabneh, A., & Tesfai, R. (2021) · Population Research and Policy Review · doi:10.1007/s11113-021-09653-8 · Cited by 9
“In addition to these graphic demonstrations of comparability, we conducted a formal test of covariate imbalance using the measure of absolute standardized difference in means (Rosenbaum, 2010).”
Method
If You Fund Them, Will They Come? Implications From a PhD Fellowship Program on Racial/Ethnic Student Diversity
Ecton, W. G., Bennett, C., Nienhusser, H. K., Castillo‐Montoya, M., & Dougherty, S. M. (2021) · AERA Open · doi:10.1177/23328584211040485 · Cited by 9
“As an additional robustness check, we also employ a randomization inference (RI) process, in which we resample, or permute, the variable of interest (here, the interaction between treated programs of study during the treatment periods) 1,000 times to obtain a stronger estimate of the likelihood of finding significant…”
BackgroundMethod
Rejective Sampling, Rerandomization, and Regression Adjustment in Survey Experiments
Yang, Z., Qu, T., & Li, X. (2021) · Journal of the American Statistical Association · doi:10.1080/01621459.2021.1984926 · Cited by 9
“In general, rerandomization with the unadjusted estimator provides more transparent analysis and helps avoid data snooping (Cox 2007; Freedman 2008; Rosenbaum 2010; Lin 2013).”
Background
The impact of Illinois’ comprehensive handheld phone ban on talking on handheld and handsfree cellphones while driving
Benedetti, M. H., Lü, B., Kinnear, N., Li, L., Delgado, M. K., & Zhu, M. (2022) · Journal of Safety Research · doi:10.1016/j.jsr.2022.11.003 · Cited by 9
On the statistical role of inexact matching in observational studies
Guo, K., & Rothenhaüsler, D. (2022) · Biometrika · doi:10.1093/biomet/asac066 · Cited by 10
Statistical matching and subclassification with a continuous dose: Characterization, algorithm, and application to a health outcomes study
Zhang, B., MacKay, E. J., & Baiocchi, M. (2023) · The Annals of Applied Statistics · doi:10.1214/22-aoas1635 · Cited by 11
“There are three key ingredients to perform a Fisher-style randomization-based test: a sharp null hypothesis, a randomized treatment assignment scheme, and a test statistic (Rosenbaum, 2002, 2010; Ding, Feller and Miratrix, 2016).”
Method
Where to Cut the Long Tail? The Value of Carrying Inventory in Online Retail
Baldauf, C., Eng‐Larsson, F., & Isaksson, O. H. D. (2020) · Management Science · doi:10.1287/mnsc.2023.4777 · Cited by 9
The Cross-Cut Statistic and its Sensitivity to Bias in Observational Studies with Ordered Doses of Treatment
Rosenbaum, P. R. (2015) · Biometrics · doi:10.1111/biom.12373 · Cited by 9
Self-citation
Foreign aid funnel? A placebo-based assessment of aid flows to non-permanent United Nations Security Council members
Reynolds, E. M. W., & Winters, M. S. (2016) · Research & Politics · doi:10.1177/2053168015626167 · Cited by 9
The Effect on Earnings of the Applied Baccalaureate Degree
Kaikkonen, D. A., & Quarles, C. L. (2018) · Community College Review · doi:10.1177/0091552118782619 · Cited by 9
“Following Rosenbaum (2010), we assume that the effects of these unmeasured traits on their probabilities of earning an AB degree are limited by the inequality: 1 1 1 Γ Γ≤ −( ) −( ) ≤ p p p p i i j j (8) Larger values of Γ imply a stronger effect of the unmeasured confounding variable.”
Background
Doing Well by Doing Good: The Impact of Foreign Aid on Foreign Public OpinionPreprint
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Authors: Rosenbaum, P. R.
Affiliations: University of Pennsylvania (US)
Corresponding author: Rosenbaum, Paul R.
ORCID: Rosenbaum, Paul R.
Venue: Springer Series in Statistics
Publisher: Springer New York
Published: 2010
ISSN: 0172-7397 (ISSN-L)
DOI: 10.1007/978-1-4419-1213-8
OpenAlex: W253646976
Cited by: 1,150
References: 12
Citations by year: 2026: 33 · 2025: 72 · 2024: 58 · 2023: 58 · 2022: 73 · 2021: 115 · 2020: 108 · 2019: 71 · 2018: 73 · 2017: 68 · 2016: 75 · 2015: 85 · 2014: 84 · 2013: 58 · 2012: 55
FWCI: 6.61
Type: book
Language: en
Open access: closed
Licence: www.springernature.com/gp/researchers/text-and-data-mining (tdm)
www.springernature.com/gp/researchers/text-and-data-mining (vor)
Locations: Springer series in statistics (publishedVersion)
CERN Document Server (European Organization for Nuclear Research) (submittedVersion)
Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)) (submittedVersion)
Funders: National Science Foundation
Topics: Physical Sciences › Mathematics › Statistics and Probability › Advanced Causal Inference Techniques
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
Social Sciences › Decision Sciences › Management Science and Operations Research › Optimal Experimental Design Methods
Keywords: observational studies, research design, causal inference, statistical inference, confounding

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