ArticleHealth services research2021
Fitting marginalized two-part models to semicontinuous survey data arising from complex samples.
Article in Health services research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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
3 citing papers in PubMed.
- Marginalized two part model for analyzing multilevel semicontinuous medical costs in Iranian households.Scientific reports · 2025Article
- Association between patient-reported social and behavioral risks and health care costs in high-risk Veterans health administration patients.Health services research · 2024Article
- Fitting marginalized two-part models to semicontinuous survey data arising from complex samples.Health services research · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
objectiveTo accurately model semicontinuous data from complex surveys, we extend marginalized two-part models to a design-based inferential framework and provide guidance on incorporating complex sample designs. DATA SOURCES: 2014 Medical Expenditure Panel Survey (MEPS). STUDY
designWe describe the use of pseudo-Maximum Likelihood Estimation and Jackknife Repeated Replication for estimating model parameters and sampling variance, respectively. We illustrate our approach using MEPS, modeling total healthcare expenditures in 2014 as a function of respondents' age and family income. We provide SAS and R code for implementing the extension, assessing model-fit indices, and evaluating the need to incorporate complex sampling features. DATA EXTRACTION
methodsData obtained from www.meps.ahrq.gov. PRINCIPLE
findingsA 100 percentage-point increase in family income as a percent of the federal poverty level was associated with a 5%-6% increase in healthcare spending. People over 65 had an increase of 4-5 times compared to those younger. Accounting for complex sampling in the models led to different parameter estimates and wider confidence intervals than the unweighted models. Ignoring complex sampling could lead to inaccurate finite population inference.
conclusionResearchers should account for complex sampling features when analyzing semicontinuous data from surveys.
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.