Reference health
Regression-adjusted matching and double-robust methods for estimating average treatment effects in health economic evaluation
59/59 checkable references clean · checked 2026-08-08
Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.
18 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.
The 59 checked references that resolve
resolves10.1177/1536867X0400400307
Implementing Matching Estimators for Average Treatment Effects in Stata
resolves10.1111/j.1468-0262.2006.00655.x
Large Sample Properties of Matching Estimators for Average Treatment Effects
resolves10.1002/sim.3150
A critical appraisal of propensity‐score matching in the medical literature between 1996 and 2003
resolves10.1002/sim.3697
Balance diagnostics for comparing the distribution of baseline covariates between treatment groups in propensity‐score matched samples
resolves10.1080/00273171.2012.640600
Using Ensemble-Based Methods for Directly Estimating Causal Effects: An Investigation of Tree-Based G-Computation
resolves10.1111/j.1541-0420.2005.00377.x
Doubly Robust Estimation in Missing Data and Causal Inference Models
resolves10.1016/j.jhealeco.2011.03.004
Economics of individualization in comparative effectiveness research and a basis for a patient-centered health care
resolves10.1177/0272989X11416988
Regression Estimators for Generic Health-Related Quality of Life and Quality-Adjusted Life Years
resolves10.1007/s10742-011-0072-8
Estimating treatment effects on healthcare costs under exogeneity: is there a ‘magic bullet’?
resolves10.1093/biostatistics/kxh020
Estimating marginal and incremental effects on health outcomes using flexible link and variance function models
resolves10.1111/j.1467-6419.2007.00527.x
SOME PRACTICAL GUIDANCE FOR THE IMPLEMENTATION OF PROPENSITY SCORE MATCHING
resolves10.1093/biomet/asn055
Dealing with limited overlap in estimation of average treatment effects
resolves10.1162/003465302317331982
Propensity Score-Matching Methods for Nonexperimental Causal Studies
resolves10.1162/REST_a_00318
Genetic Matching for Estimating Causal Effects: A General Multivariate Matching Method for Achieving Balance in Observational Studies
resolves10.1002/hec.903
Cost‐effectiveness acceptability curves – facts, fallacies and frequently asked questions
resolves10.1007/s10742-012-0090-1
Bias and variance trade-offs when combining propensity score weighting and regression: with an application to HIV status and homeless men
resolves10.1111/j.1475-6773.2008.00834.x
Evaluating Health Care Programs by Combining Cost with Quality of Life Measures: A Case Study Comparing Capitation and Fee for Service
resolves10.1023/A:1020371312283
Estimation of Causal Effects using Propensity Score Weighting: An Application to Data on Right Heart Catheterization
resolves10.1111/1468-0262.00442
Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score
resolves10.1093/pan/mpl013
Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference
resolves10.1177/0272989X11406986
A Framework for Addressing Structural Uncertainty in Decision Models
resolves10.1214/07-STS227
Demystifying Double Robustness: A Comparison of Alternative Strategies for Estimating a Population Mean from Incomplete Data
resolves10.1177/0272989X12448929
Methods for Estimating Subgroup Effects in Cost-Effectiveness Analyses That Use Observational Data
resolves10.1002/hec.2806
STATISTICAL METHODS FOR COST‐EFFECTIVENESS ANALYSES THAT USE OBSERVATIONAL DATA: A CRITICAL APPRAISAL TOOL AND REVIEW OF CURRENT PRACTICE
resolves10.1002/sim.1903
Stratification and weighting via the propensity score in estimation of causal treatment effects: a comparative study
resolves10.1016/j.jhealeco.2004.09.011
Generalized modeling approaches to risk adjustment of skewed outcomes data
resolves10.1002/hec.1477
Non‐parametric methods for cost‐effectiveness analysis: the central limit theorem and the bootstrap compared
resolves10.1002/hec.1008
Methods for incorporating covariate adjustment, subgroup analysis and between‐centre differences into cost‐effectiveness evaluations
resolves10.1177/0962280210386207
Diagnosing and responding to violations in the positivity assumption
resolves10.1515/1557-4679.1382
Evaluating treatment effectiveness in patient subgroups: a comparison of propensity score methods with an automated matching approach
resolves10.1080/01621459.1994.10476818
Estimation of Regression Coefficients When Some Regressors are not Always Observed
resolves10.1214/07-STS227D
Comment: Performance of Double-Robust Estimators When “Inverse Probability” Weights Are Highly Variable
resolves10.1080/01621459.1995.10476493
Analysis of Semiparametric Regression Models for Repeated Outcomes in the Presence of Missing Data
resolves10.1093/biomet/70.1.41
The central role of the propensity score in observational studies for causal effects
resolves10.2307/2529685
The Use of Matched Sampling and Regression Adjustment to Remove Bias in Observational Studies
resolves10.1002/sim.2739
The design <i>versus</i> the analysis of observational studies for causal effects: parallels with the design of randomized trials
resolves10.1080/01621459.2000.10474233
Combining Propensity Score Matching with Additional Adjustments for Prognostic Covariates
resolves10.1186/cc10468
Is Drotrecogin alfa (activated) for adults with severe sepsis, cost-effective in routine clinical practice?
resolves10.18637/jss.v042.i07
Multivariate and Propensity Score Matching Software with Automated Balance Optimization: The<b>Matching</b>Package for<i>R</i>
resolves10.1002/hec.1748
A matching method for improving covariate balance in cost‐effectiveness analyses
resolves10.1002/sim.3818
Comparative effectiveness research: Policy context, methods development and research infrastructure
resolves10.1016/j.jclinepi.2009.11.020
Propensity score estimation: neural networks, support vector machines, decision trees (CART), and meta-classifiers as alternatives to logistic regression
resolves10.1002/hec.843
Regression methods for covariate adjustment and subgroup analysis for non‐censored cost‐effectiveness data
The 18 references without a DOI — listed, not checked
no DOI — not checkedAbadie, A., Herr, J.L., Imbens, G.W., Drukker, D.M.: NNMATCH: Stata module to compute nearest-neighbor bias-corrected estimators. http://fmwww.bc.edu/repec/bocode/n/nnmatch.hlp (2004b). Accessed 15 June 2012
no DOI — not checkedBusso, M., DiNardo, J., McCrary, J.: New evidence on the finite sample properties of propensity score reweighting and matching estimators. In: Working paper, vol. 3998, 2011
no DOI — not checkedFung, V., Brand, R.J., Newhouse, J.P., Hsu, J.: Using medicare data for comparative effectiveness research: opportunities and challenges. Am. J. Manag. Care 17(7), 489–496 (2011)
no DOI — not checkedGlick, H., Doshi, J., Sonnad, S., Polsky, D.: Economic Evaluation in Clinical Trials. Oxford University Press, Oxford (2007)
no DOI — not checkedGruber, S., van der Laan, M.J.: An application of collaborative targeted maximum likelihood estimation in causal inference and genomics. Int. J. Biostat. 6(1), Article 18 (2010). doi: 10.2202/1557-4679.1182
no DOI — not checkedJones, A., Lomas, J., Rice, N.: Applying beta-type size distributions to healthcare cost regressions. In: HEDG working papers, vol. WP 11/31. HEDG, c/o Department of Economics, University of York, 2011
no DOI — not checkedJones, A.M.: Models for health care. In: HEDG working papers. HEDG, c/o Department of Economics, University of York, 2010
no DOI — not checkedManca, A., Austin, P.C.: Using propensity score methods to analyse individual patient-level cost-effectiveness data from observational studies. http://www.york.ac.uk/res/herc/documents/wp/08_20.pdf (2008). Accessed 15 June 2012
no DOI — not checkedMihaylova, B., Briggs, A., O’Hagan, A., Thompson, S.: Review of statistical methods for analysing healthcare resources and costs. Health Econ. (2010). doi: 10.1002/hec.1653
no DOI — not checkedNICE: Guide to the methods of technology appraisal 2013. http://www.nice.org.uk/media/D45/1E/GuideToMethodsTechnologyAppraisal2013.pdf (2013). Accessed 10 July 2013
no DOI — not checkedPorter, K.E., Gruber, S., Laan, M.J.V.D., Sekhon, J.S.: The relative performance of targeted maximum likelihood estimators. Int. J. Biostat. (2011). doi: 10.2202/1557-4679
no DOI — not checkedQuinn, C.: The health-economic applications of copulas: methods in applied econometric research. http://ideas.repec.org/p/yor/hectdg/07-22.html (2007). Accessed 10 Aug 2011
no DOI — not checkedR Development Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna (2011)
no DOI — not checkedStataCorp: Stata Statistical Software: Release 12. StataCorp LP, College Station (2011)
no DOI — not checkedTrivedi, P.K., Zimmer, D.M.: Copula Modeling: An Introduction to Practitioners, vol. 1. Foundations and Trends in Econometrics. Now Publishing Inc., Delft (2005)
no DOI — not checkedvan der Laan, M.J.: Targeted maximum likelihood based causal inference: part I. Int. J. Biostat. (2010). doi: 10.2202/1557-4679.1211
no DOI — not checkedvan der Laan, M.J., Gruber, S.: Collaborative double robust targeted maximum likelihood estimation. Int. J. Biostat. (2010). doi: 10.2202/1557-4679.1181
no DOI — not checkedvan der Laan, M.J., Polley, E.C., Hubbard, A.E.: Super learner. Stat. Appl. Genet. Mol. Biol. (2007). doi: 10.2202/1544-6115.1309
What this badge says. CiteStamped means the CHECKABLE references of this
work were clean at the dated check: each resolved to a known work in a public registry, and none
carried a retraction notice at that time. It says nothing about the quality, findings,
or importance of the work itself, and nothing about references deposited without a DOI.
checked 2026-08-08 — re-checked daily as this page is visited; titles and statuses come from Crossref and DataCite and are not part of the signed record
Embed this badge
Both snippets point at the live badge image and link back to this page. The badge re-renders from the daily check, so an embed never goes stale by more than a day of visits.
<a href="https://citestamp.com/citestamped/10.1007/s10742-013-0109-2"><img src="https://citestamp.com/citestamped/10.1007/s10742-013-0109-2/badge.svg" alt="CiteStamped reference-health badge" width="460" height="64"></a>
[](https://citestamp.com/citestamped/10.1007/s10742-013-0109-2)