Results 1 to 10 of about 277 (152)

Testing for treatment effect twice using internal and external controls in clinical trials [PDF]

Journal of Causal Inference, 2023
Leveraging external controls – relevant individual patient data under control from external trials or real-world data – has the potential to reduce the cost of randomized controlled trials (RCTs) while increasing the proportion of trial patients given ...
Yi Yanyao, Zhang Ying, Du Yu, Ye Ting
doaj   +2 more sources

Why decision curves cross treat-all and treat-none: A PPV and calibration perspective [PDF]

Global Epidemiology
Net benefit is widely used to assess whether clinical prediction models can improve decision-making, but its interpretation is often difficult in practice.
Linard Hoessly
doaj   +2 more sources

Generalized coarsened confounding for causal effects: a large-sample framework [PDF]

Journal of Causal Inference
There has been widespread use of causal inference methods for the rigorous analysis of observational studies and to identify policy evaluations. In this article, we consider a class of generalized coarsened procedures for confounding.
Ghosh Debashis, Wang Lei
doaj   +2 more sources

Impact of supervisors' research style on young biomedical scientists' capacity development as measured by REDi, a novel index of crossdisciplinarity [PDF]

Frontiers in Research Metrics and Analytics, 2022
The challenge for medical schools in Japan is to develop research activities for innovation. This study aimed at analyzing the connection between the research output of “promising researchers” (next-generation leaders in terms of research activity) and ...
Akiko Hashiguchi, Hiroka Hamada, Satoru Takahashi, Keisuke Honda   +3 more
doaj   +2 more sources

Discovery of critical thresholds in mixed exposures and estimation of policy intervention effects [PDF]

Journal of Causal Inference
Regulations of chemical exposures often focus on individual substances, neglecting the amplified toxicity that can arise from multiple concurrent exposures.
McCoy David B., Hubbard Alan, van der Laan Mark, Schuler Alejandro   +3 more
doaj   +2 more sources

Bounding causal effects with an unknown mixture of informative and non-informative missingness [PDF]

Journal of Causal Inference
In experimental and observational data settings, researchers often have limited knowledge of the reasons for missing outcomes. To address this uncertainty, we propose bounds on causal effects for missing outcomes, accommodating the scenario where ...
Rubinstein Max, Agniel Denis, Han Larry, Horvitz-Lennon Marcela, Normand Sharon-Lise   +4 more
doaj   +2 more sources

Semiparametric discovery and estimation of interaction in mixed exposures using stochastic interventions [PDF]

Journal of Causal Inference
Understanding the complex interactions among multiple environmental exposures is critical for assessing their combined impact on health outcomes. This study introduces InterXshift, a novel semiparametric method that provides a nonparametric definition of
McCoy David B., Hubbard Alan, van der Laan Mark, Schuler Alejandro   +3 more
doaj   +2 more sources

A novel Weighted Exponential-Lindley distribution with Bayesian estimation under progressive Type-II censoring and a Bayesian-Calibrated Variational Autoencoder for survival prediction [PDF]

Frontiers in Artificial Intelligence
One-parameter lifetime models, such as the exponential and Lindley distributions, and two-parameter extensions such as the weighted Lindley distribution cannot separately control tail weight and dispersion, since a single shape parameter governs both. We
P. Furqan Ahmed, V. Sujatha
doaj   +2 more sources

Assessing surrogate heterogeneity in real world data using meta-learners [PDF]

Journal of Causal Inference
Surrogate markers are most commonly studied within the context of randomized clinical trials. However, the need for alternative outcomes also extends to real-world public health and social science research, where randomized trials are often impractical ...
Knowlton Rebecca, Parast Layla
doaj   +2 more sources

The structural properties of the Gompertz-two-parameter-Lindley distribution and associated inference

Open Mathematics, 2022
In this article, we propose a Gompertz-two-parameter-Lindley distribution by mixing the frailty parameter of the Gompertz distribution with a two-parameter Lindley distribution. The structural properties of the model, such as shape properties, cumulative
Ou Xionghui, Lu Hezhi, Kong Jingsen
doaj   +1 more source