ArticleJournal of statistical theory and practice2013
Bias Correction Methods for Misclassified Covariates in the Cox Model: comparison offive correction methods by simulation and data analysis.
Article in Journal of statistical theory and practice, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- Misclassification simulation extrapolation method for a Weibull accelerated failure time model.Statistical methods in medical research · 2023Article
- Noninterventional studies in the COVID-19 era: methodological considerations for study design and analysis.Journal of clinical epidemiology · 2023Article
- Simulation extrapolation method for measurement error: A review.Statistical methods in medical research · 2022Review
- Addressing Measurement Error in Random Forests Using Quantitative Bias Analysis.American journal of epidemiology · 2021Article
- Pharmacoepidemiology for nephrologists (part 2): potential biases and how to overcome them.Clinical kidney journal · 2021Review
- Regression on imperfect class labels derived by unsupervised clustering.Briefings in bioinformatics · 2021Article
- Article
- STRATOS guidance document on measurement error and misclassification of variables in observational epidemiology: Part 2-More complex methods of adjustment and advanced topics.Statistics in medicine · 2020Article
- Epidemiologic analyses with error-prone exposures: review of current practice and recommendations.Annals of epidemiology · 2018Review
- Random Guess and Wishful Thinking are the Best Blinding Scenarios.Contemporary clinical trials communications · 2016Article
- Are all biases missing data problems?Current epidemiology reports · 2015Article
- Misclassification in administrative claims data: quantifying the impact on treatment effect estimates.Current epidemiology reports · 2014Article
- Assessing the Impacts of Misclassified Case-Mix Factors on Health Care Provider Profiling: Performance of Dialysis Facilities.Inquiry : a journal of medical care organization, provision and financingArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Measurement error/misclassification is commonplace in research when variable(s) can notbe measured accurately. A number of statistical methods have been developed to tackle this problemin a variety of settings and contexts. However, relatively few methods are available to handlemisclassified categorical exposure variable(s) in the Cox proportional hazards regression model. Inthis paper, we aim to review and compare different methods to handle this problem - naïvemethods, regression calibration, pooled estimation, multiple imputation, corrected score estimation,and MC-SIMEX - by simulation. These methods are also applied to a life course study with recalleddata and historical records. In practice, the issue of measurement error/misclassification should beaccounted for in design and analysis, whenever possible. Also, in the analysis, it could be moreideal to implement more than one correction method for estimation and inference, with properunderstanding of underlying assumptions.
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.