Research Students (for MS thesis in Applied Statistics):

• Raisa Shamma (2020-2021): Information criteria for penalized likelihood approach in generalized linear models
• Safwan Shihab (2019-2020): Estimating causal effect of time dependent exposure on survival outcome.
• Silvia Khanam (2019-2020): On the second order bias reduction in the generalized linear models.
• Argha Dhar (2019-2020): Evaluation of the methods for estimating causal effect with binary outcome : A simulation study.
• Ariful Islam Sanim (2018-2019): On estimating average treatment effect of rare exposure in observational studies: sample size consideration and bias correction.
• Md. Rasel (2018-2019): Dynamic prediction using landmark model: A simulation study to evaluate performance of different landmark approaches.
• Tasneem Fatima Alam (2017-2018): Estimation and Inference for Accelerated Failure Time (AFT) models with small or rare event survival data.
• Nowrin Nusrat (2017-2018): Dealing with separation or near-to-separation in the model for multinomial response.
• Ema Akter (2017-2018):  Using Jeffreys-and logF(1,1)-prior based penalized methods for propensity score models with rare exposure.
• Muntaha Mushfiquee (2016-2017):  Propensity score based adjustment for covariate effects on classification accuracy of biomarker using ROC curve.
• Tanzila Rahman Mou (2016-2017): Using penalized methods for propensity score model with rare exposure in observation studies with binary outcome.
• Momenul Haque Mondol (2015-2016): Bias reduced and separation-proof  generalized estimating equation for correlated binary data.
• Avizit Adhikary (2015-2016): Application of Firth’s type penalized method to Cox PH framework for developing predictive models with sparse or highly censored survival data.
• Md. Maidul Husain (2015-2016): Covariates adjusted area under ROC curve in the presence of measurement error.
• Mahbuba Sultana (2014-2015):  An evaluation of penalized likelihood methods for developing binary risk models with rare events.
• Md. Moniruzzaman (2014-2015): Prediction in the random effects logistic model for clustered binary data.
• Afrin Sadia Rumana (2013-2014): Concordance measures for evaluating the added predictive ability of new risk factors in logistic regression models: An alternative to the existing measures.
• Mohammad Junayed Bhuyan (2013-2014): Generalized Bernoulli model for correlated binary responses with an application to child nutrition data in Bangladesh
• Tanjina Rahman (2013-2014): Concordance statistics for evaluating the predictive performance of stratified Cox proportional hazard models.
• Biplob Biswas (2012-2013):  Concordance statistics and discrimination in logistic regression models.
• Ariful Bhuiyan (2012-2013): Measures of predictive accuracy and explained variation for survival risk models.

Funded Research:

• Geographical variation in the prevalence and pattern of chronic diseases in Bangladesh: A Bayesian spatial analysis of national health survey data (2021). DU Centennial Research Grant.
• Disease Mapping in Bangladesh (2015): A case study with hypertension and diabetes. DU Research Grant.