Abu Manju PhD

Abu Manju PhD
Position
Lecturer
Country of Origin

Bangladesh

Availability
By appointment
Background

Abu Manju, PhD, graduated with his first degree in Statistics, then completed an MSc in Statistics at the University of Chittagong, Bangladesh, followed by a PhD in Biostatistics at the University of Maastricht, the Netherlands, in 2016. His doctoral thesis considered the development and application of statistical methods for optimally designing the nested cost-effectiveness randomised clinical trials. In June 2016, Abu started working as a postdoctoral fellow at the Centre for Mathematical Sciences (CMS), MSD in Oss, the Netherlands. In this role, he performed statistical research to develop appropriate performance measures, criteria, and experimental designs for the robustness of microbiological methods. He also works as a lecturer at Wittenborg University of Applied Sciences.

Biography
  • Manju, M.A., Ijzerman, P., & Van den Heuvel, E.R. (2017). A comparison of dilution experiments to estimate the detection proportion of qualitative microbiological methods. Journal of Biopharmaceuticals Statistics (submitted for publication).
  • Manju, M.A., Candel, M.J.J.M., & Berger, M.P.F. (2014). Sample size calculation in cost-effectiveness cluster randomized trials: optimal and maximin approaches. Statistics in Medicine, 33(15): 2538-2553.
  • Manju, M.A., Candel, M.J.J.M., & Berger, M.P.F. (2015). Optimal and maximin sample sizes for multicentre cost-effectiveness trials. Statistical Methods in Medical Research, 24(5): 513-539.
  • Manju, M.A., Candel, M.J.J.M., & van Breukelen, J.G.P. (2017). SamP2CeT: An interactive computer program for sample size and power calculation for two-level cost-effectiveness trials. Journal of Health Economics (under review).
  • Manju, M.A., Candel, M.J.J.M., & van Breukelen, J.G.P. (2017). Robustness of cost-effectiveness analyses of cluster randomized trials against skewed cost data. Statistics in Medicine (under review).
  • Manju, M.A., & Biswas, S.C. (2011). Comparison of power values in generalized linear mixed model (GLMM) under the different estimation methods. International Journal of Current Research, 3: 182-188.
  • Biswas, S.C. & Manju, M.A., (2013-2014). A simulation study for comparing the power of Wald test for cluster binary data analysis. Chittagong University Journal of Science, 36: 89-101.
Expertise / Subjects
Business Statistics.