Outputs (6)

Improving power calculations in educational trials (2023)
Report
Singh, A., Uwimpuhwe, G., Vallis, D., Akhter, N., Coolen-Maturi, T., Einbeck, J., Higgins, S., Culliney, M., & Demack, S. (2023). Improving power calculations in educational trials. Education Endowment Foundation

The aim of this study was to investigate and empirically derive parameters commonly used for statistical power and sample size calculations to better inform future trial design. Towards achieving this aim, the research project leveraged the richness... Read More about Improving power calculations in educational trials.

Individual participant data meta-analysis: pooled effect of EEF funded educational trials on low baseline attaining group (2023)
Presentation / Conference Contribution
Uwimpuhwe, G., Singh, A., Akhter, N., Ashraf, B., Coolen-Maturi, T., Robinson, T., Higgins, S., & Einbeck, J. (2023, July). Individual participant data meta-analysis: pooled effect of EEF funded educational trials on low baseline attaining group. Presented at International Workshop on Statistical Modelling, Dortmund

The Education Endowment Foundation (EEF), a charity aiming to break the link between socioeconomic disadvantage and pupil attainment, has commissioned over 200 randomised controlled trials. The collection of data from these trials, the `EEF Data Arch... Read More about Individual participant data meta-analysis: pooled effect of EEF funded educational trials on low baseline attaining group.

Smoothed bootstrap methods for bivariate data (2023)
Journal Article
Al Luhayb, A., Coolen-Maturi, T., & Coolen, F. (2023). Smoothed bootstrap methods for bivariate data. Journal of statistical theory and practice, 17(3), Article 37. https://doi.org/10.1007/s42519-023-00334-7

A smoothed bootstrap method is introduced for right-censored data based on the rightcensoring-A(n) assumption introduced by Coolen and Yan (2004), which is a generalization of Hill’s A(n) assumption (Hill, 1968) for right-censored data. The smoothed... Read More about Smoothed bootstrap methods for bivariate data.

A generalized system reliability model based on survival signature and multiple competing failure processes (2023)
Journal Article
Chang, M., Coolen, F., Coolen-Maturi, T., & Huang, X. (online). A generalized system reliability model based on survival signature and multiple competing failure processes. Journal of Computational and Applied Mathematics, 435, Article 115364. https://doi.org/10.1016/j.cam.2023.115364

Degradation-based system reliability analysis has been extensively conducted, but the components in a system are assumed to experience similar degradation and shock processes, neglecting actual failure mechanisms. However, multiple types of component... Read More about A generalized system reliability model based on survival signature and multiple competing failure processes.

New reliability model for complex systems based on stochastic processes and survival signature (2023)
Journal Article
Chang, M., Huang, X., Coolen, F., & Coolen-Maturi, T. (2023). New reliability model for complex systems based on stochastic processes and survival signature. European Journal of Operational Research, 309(3), 1349-1364. https://doi.org/10.1016/j.ejor.2023.02.027

For systems with complicated structures, reliability analysis based on survival signature has been carried out by modelling time-to-failure data with specific distributions. However, for highly reliable systems, only little or no failure data may be... Read More about New reliability model for complex systems based on stochastic processes and survival signature.

Smoothed Bootstrap for Right-Censored Data (2023)
Journal Article
Luhayb, A. S. M. A., Coolen, F. P., & Coolen-Maturi, T. (2024). Smoothed Bootstrap for Right-Censored Data. Communications in Statistics - Theory and Methods, 53(11), 4037-4061. https://doi.org/10.1080/03610926.2023.2171708

A smoothed bootstrap method is introduced for right-censored data based on the right-censoring-A(n) assumption introduced by Coolen and Yan, which is a generalization of Hill’s A(n) assumption for right-censored data. The smoothed bootstrap method is... Read More about Smoothed Bootstrap for Right-Censored Data.