ArticleBMJ open2020
Introduction to statistical simulations in health research.
Article in BMJ open, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.
What it found
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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.
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Who cites it
29 citing papers in PubMed.
- Methods for Adjusting for Covariate Measurement Error in Flexible Modeling of Functional Form: Designing a Blinded, Controlled Neutral Comparison Simulation Study.Biometrical journal. Biometrische Zeitschrift · 2026Article
- Article
- Toward Evidence Synthesis of Adverse Events in Imbalanced Time-to-Event Data.Journal of evidence-based medicine · 2026Article
- The Effect of Changing Weekly Contact Training Duration Beyond Current Guidelines on Head Acceleration Events in Rugby Union.Sports medicine (Auckland, N.Z.) · 2026Article
- A two-phase clustering procedure based on allele specific expression.BMC bioinformatics · 2026Article
- Clinical Trial Simulation: Planning With the OCTAVE Framework, Implementation and Validation Principles.Statistics in medicine · 2026Article
- A Methodological Review of Simulation Studies Published in Pharmacoepidemiology and Drug Safety.Pharmacoepidemiology and drug safety · 2026Review
- Evaluating Methods for High-Dimensional Mediation in Metabolomics Data.Environmental science & technology · 2026Article
- Responsible data selection method for algorithmic personalization of health apps: a case study on promoting mental health.Frontiers in digital health · 2026Article
- Development of a decision tree diagram for classifying study designs in tumour pathology research: a multidisciplinary approach.The journal of pathology. Clinical research · 2026Article
- Identifying relevant intersections in relation to motivation and attempt to stop smoking by using a combination of methods to develop robust predictive models and resampling techniques: A cross-sectional study of the German population.Addiction (Abingdon, England) · 2025Article
- Comparison of statistical methods for the analysis of patient-reported outcomes (PROs), particularly the Short-Form 36 (SF-36), in randomised controlled trials (RCTs) using standardised effect size (SES): an empirical analysis.Health and quality of life outcomes · 2025Article
- Efficiency of case-crossover versus time-series study designs for extreme heat exposures.Environmental epidemiology (Philadelphia, Pa.) · 2025Article
- A Statistical Framework to Detect and Quantify Operator-Learning Curves in Medical Device Safety Evaluation.Medical devices (Auckland, N.Z.) · 2025Article
- Article
- Proposal of an alternative way of reporting the results of comparative simulation studies.Frontiers in psychology · 2025Article
- Comparison of statistical methods for the analysis of patient-reported outcomes in randomised controlled trials: A simulation study.Statistical methods in medical research · 2024Article
- Many nonnormalities, one simulation: Do different data generation algorithms affect study results?Behavior research methods · 2024Article
- A transformer model for cause-specific hazard prediction.BMC bioinformatics · 2024Article
- Statistical inference for diagnostic test accuracy studies with multiple comparisons.Statistical methods in medical research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
In health research, statistical methods are frequently used to address a wide variety of research questions. For almost every analytical challenge, different methods are available. But how do we choose between different methods and how do we judge whether the chosen method is appropriate for our specific study? Like in any science, in statistics, experiments can be run to find out which methods should be used under which circumstances. The main objective of this paper is to demonstrate that simulation studies, that is, experiments investigating synthetic data with known properties, are an invaluable tool for addressing these questions. We aim to provide a first introduction to simulation studies for data analysts or, more generally, for researchers involved at different levels in the analyses of health data, who (1) may rely on simulation studies published in statistical literature to choose their statistical methods and who, thus, need to understand the criteria of assessing the validity and relevance of simulation results and their interpretation; and/or (2) need to understand the basic principles of designing statistical simulations in order to efficiently collaborate with more experienced colleagues or start learning to conduct their own simulations. We illustrate the implementation of a simulation study and the interpretation of its results through a simple example inspired by recent literature, which is completely reproducible using the R-script available from online supplemental file 1.
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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.