Bayesian Inference: Statistical Gimmick or Added Value?

JOHNSON, SINDHU R.

doi:10.3899/jrheum.110013

Cited by 3 publications

(2 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Further, the numbers of events may be small. The small sample size can affect the ability to use conventional methodologic and statistical approaches to make inferences about treatment effects or risk estimates 1,5,6,7,8,9 .…”

mentioning

confidence: 99%

Propensity Score Methods in Rare Disease: A Demonstration Using Observational Data in Systemic Lupus Erythematosus

et al. 2020

Self Cite

View full text Add to dashboard Cite

Observational studies allow researchers to understand the natural history of rheumatic conditions, risk factors for disease development, factors affecting important disease-related outcomes and estimate treatment effect from real world data. However, this design carries a risk of confounding bias. A propensity score is a balancing score that aims to minimize the difference between study groups and consequently potential confounding effects. The score can be applied in one of four methods in observational research: matching, stratification, adjustment, and inverse probability weighting. Systemic lupus erythematosus (SLE) is a rare disease characterized by relatively small sample size and/or low event rates. In this article, we review propensity score methods. We demonstrate application of propensity score methods to achieve study group balance in a rare disease using an example of risk of infection in SLE patients with hypogammaglobulinemia.

show abstract

mentioning

confidence: 99%

Propensity Score Methods in Rare Disease: A Demonstration Using Observational Data in Systemic Lupus Erythematosus

et al. 2020

Self Cite

View full text Add to dashboard Cite

show abstract

“…It is a different way to analyze data: allowing inferences to be made using the available data. Bayesian methods are increasingly being used in observational studies (5, 6) and clinical trials (7, 8). Indeed, the US Food and Drug Administration has guidelines for the use of Bayesian methods in medical device clinical trials (9).…”

Section: General Principles Of Trial Designmentioning

confidence: 99%