ArticleStatistics in medicine2016
Propensity score and doubly robust methods for estimating the effect of treatment on censored cost.
Article in Statistics in medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.
- Performance of propensity score methods in observational studies: a systematic review.Systematic reviews · 2026Pooled it
- Estimating Healthcare Expenditure Using Parametric Change Point Models.Journal of data science : JDS · 2025Article
- Statistical methods for assessing treatment effects on ordinal outcomes using observational data.Communications in statistics: Simulation and computation · 2025Article
- Evaluation of the causal effect of maternal education on the utilisation of maternal health services in Bangladesh using an observational study - a comparison of different propensity score methods and covariate adjustment.Archives of public health = Archives belges de sante publique · 2024Article
- Validation of causal inference data using DirectLiNGAM in an environmental small-scale model and calculation settings.MethodsX · 2024Article
- An outcome-wide analysis of the effects of diagnostic labeling of Alzheimer's disease and related dementias on social relationships.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2024Article
- Estimating Treatment Effect of Adjuvant Chemotherapy in Elderly Patients With Stage III Colon Cancer Using Bayesian Networks.JCO clinical cancer informatics · 2023Article
- Dealing with confounding in observational studies: A scoping review of methods evaluated in simulation studies with single-point exposure.Statistics in medicine · 2023Article
- Cost data in implementation science: categories and approaches to costing.Implementation science : IS · 2022Article
- Net benefit separation and the determination curve: A probabilistic framework for cost-effectiveness estimation.Statistical methods in medical research · 2021Article
- Nested g-computation: A causal approach to analysis of censored medical costs in the presence of time-varying treatment.Journal of the Royal Statistical Society. Series C, Applied statistics · 2020Article
- Analyzing medical costs with time-dependent treatment: The nested g-formula.Health economics · 2018Observational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
The estimation of treatment effects on medical costs is complicated by the need to account for informative censoring, skewness, and the effects of confounders. Because medical costs are often collected from observational claims data, we investigate propensity score (PS) methods such as covariate adjustment, stratification, and inverse probability weighting taking into account informative censoring of the cost outcome. We compare these more commonly used methods with doubly robust (DR) estimation. We then use a machine learning approach called super learner (SL) to choose among conventional cost models to estimate regression parameters in the DR approach and to choose among various model specifications for PS estimation. Our simulation studies show that when the PS model is correctly specified, weighting and DR perform well. When the PS model is misspecified, the combined approach of DR with SL can still provide unbiased estimates. SL is especially useful when the underlying cost distribution comes from a mixture of different distributions or when the true PS model is unknown. We apply these approaches to a cost analysis of two bladder cancer treatments, cystectomy versus bladder preservation therapy, using SEER-Medicare data. Copyright © 2015 John Wiley & Sons, Ltd.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.