ArticleEnvironmental science & technology2021
Censoring Trace-Level Environmental Data: Statistical Analysis Considerations to Limit Bias.
Article in Environmental science & technology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 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
15 citing papers in PubMed.
- Per- and polyfluoroalkyl substances (PFAS) exposure profiles for pregnant women living in urban, rural, and remote areas of Suriname, South America suggest higher serum concentrations in remote rainforest communities.Journal of exposure science & environmental epidemiology · 2026Article
- Linking magnetic susceptibility with polycyclic aromatic hydrocarbon concentrations in urban road dust: a proxy-based approach for contamination monitoring.Environmental geochemistry and health · 2026Article
- Rare Earth Elements and Technology-Related Trace Metals in Paediatric Scalp Hair: A 2001 Urban Baseline from Spain.Journal of xenobiotics · 2026Article
- Analysis of Human Placental Tissues Using Gas Chromatography High Resolution Accurate Mass Spectrometry to Characterize Exposure to a Range of Semivolatile Organic Compounds.Exposure and health · 2026Article
- Archetypes of Spatial Concentration Variability of Organic Contaminants in the Atmosphere: Implications for Identifying Sources and Mapping the Gaseous Outdoor Inhalation Exposome.Environmental science & technology · 2024Article
- Ethylene Oxide: An Air Contaminant of Concern.ACS ES&T air · 2024Review
- Per- and polyfluoroalkyl substances (PFAS) in paired tap water and house dust from United States homes.Indoor environments · 2024Article
- Prioritization and Risk Ranking of Regulated and Unregulated Chemicals in US Drinking Water.Environmental science & technology · 2024Article
- Assessing lead exposure in U.S. pregnant women using biological and residential measurements.The Science of the total environment · 2023Article
- Separating Measurement Error and Signal in Environmental Data: Use of Replicates to Address Uncertainty.Environmental science & technology · 2023Article
- Characterizing surface water concentrations of hundreds of organic chemicals in United States for environmental risk prioritization.Journal of exposure science & environmental epidemiology · 2023Article
- Freshwater Environmental Risk Assessment of Down-the-Drain Octinoxate Emissions in the United States.Environmental toxicology and chemistry · 2022Review
- Bayesian inference of chemical exposures from NHANES urine biomonitoring data.Journal of exposure science & environmental epidemiology · 2022Article
- Field Validation of a Novel Passive Sampler for Dissolved PFAS in Surface Waters.Environmental toxicology and chemistry · 2022Article
- Response to Comment on "Censoring Trace-Level Environmental Data: Statistical Analysis Considerations to Limit Bias".Environmental science & technology · 2021Article
Corrections and comments
- Commented on by
- Commented on by
Authors and funding
8 authors.
Funding
Abstract
Trace-level environmental data typically include values near or below detection and quantitation thresholds where health effects may result from low-concentration exposures to one chemical over time or to multiple chemicals. In a cook stove case study, bias in dibenzo[a,h]anthracene concentration means and standard deviations (SDs) was assessed following censoring at thresholds for selected analysis approaches: substituting threshold/2, maximum likelihood estimation, robust regression on order statistics, Kaplan-Meier, and omitting censored observations. Means and SDs for gas chromatography-mass spectrometry-determined concentrations were calculated after censoring at detection and calibration thresholds, 17% and 55% of the data, respectively. Threshold/2 substitution was the least biased. Measurement values were subsequently simulated from two log-normal distributions at two sample sizes. Means and SDs were calculated for 30%, 50%, and 80% censoring levels and compared to known distribution counterparts. Simulation results illustrated (1) threshold/2 substitution to be inferior to modern after-censoring statistical approaches and (2) all after-censoring approaches to be inferior to including all measurement data in analysis. Additionally, differences in stove-specific group means were tested for uncensored samples and after censoring. Group differences of means tests varied depending on censoring and distributional decisions. Investigators should guard against censoring-related bias from (explicit or implicit) distributional and analysis approach decisions.
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.