Bayesian methods are becoming increasingly in demand in clinical and public health comparative effectiveness research. Limited literature has explored parametric Bayesian causal approaches to handle time-dependent treatment and time-dependent covariates. In this article, building on to the work on Bayesian g-computation, we propose a fully Bayesian causal approach, implemented using latent confounder classes which represent the patient's disease and health status. Our setting is suitable when the latent class represents a true disease state that the physician is able to infer without misclassification based on manifest variables. We consider a causal effect that is confounded by the visit-specific latent class in a longitudinal setting and formulate the joint likelihood of the treatment, outcome and latent class models conditionally on the class indicators. The proposed causal structure with latent classes features dimension reduction of time-dependent confounders. We examine the performance of the proposed method using simulation studies and compare the proposed method to other causal methods for longitudinal data with time-dependent treatment and time-dependent confounding. Our approach is illustrated through a study of the effectiveness of intravenous immunoglobulin in treating newly diagnosed juvenile dermatomyositis.

Kuan Liu

Olli Saarela

George Tomlinson

Brian M Feldman

Eleanor Pullenayegum

Statistical Methods in Medical Research

STATISTICAL METHODS IN MEDICAL RESEARCH 是一份同行评审的学术期刊，是医学统计学所有主要领域文章的主要载体，也是所有医学统计学家的重要参考资料。这本独特的期刊只专注于统计和医学，旨在让专业人士了解医学界现在可以使用的许多强大的统计技术。该期刊是出版伦理委员会 (COPE) 的成员

Statistical Methods in Medical Research is a peer-reviewed academic journal that serves as a primary platform for articles in all major areas of medical statistics, making it an essential reference for all medical statisticians. This unique journal focuses exclusively on the intersection of statistics and medicine, aiming to inform professionals about the many powerful statistical techniques currently available in the medical field. Furthermore, the journal is a member of the Committee on Publication Ethics (COPE).

《Statistical Methods in Medical Research》是一本经过同行评审的学术期刊，涵盖医学统计学的所有主要领域，成为医学统计学家们的重要参考资料。这本独特的期刊专注于统计学与医学的结合，旨在帮助专业人士了解医学界当前可用的多种强大统计技术。此外，该期刊还是出版伦理委员会（COPE）的成员。

Category	Quartile
医学	3
医学, 数学与计算生物学	2
医学, 统计学与概率论	3
医学, 卫生保健与服务	4
医学, 医学信息	4

A Bayesian latent class approach to causal inference with longitudinal data

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Journal Info

Category	Quartile
STATISTICS & PROBABILITY	1