Personal profile
Research interests
Joint Modeling of Longitudinal and Time to Event Data, Dynamic Risk Prediction,, Missing Data Analysis, High-Dimensional Data Analysis, Variable Selection, Computational Statistics, Bayesian Statistics
Teaching
MATH48221 / MATH68221: Bayesian Statistics – Year 4 undergraduate and Master’s level students, University of Manchester.
Supervision information
Master’s Dissertations Supervised
-
Chen Ling – Standard and Penalized Generalized Estimating Equations for Longitudinal Data: Methods, Simulations, and Applications, The University of Manchester, Sep 2025.
-
Daniel Hearne-Potton – Leveraging Machine Learning and Deep Learning for Longitudinal Data Analysis: A Comparative Evaluation of Traditional and Modern Approaches, The University of Manchester, Sep 2025.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
-
SDG 1 No Poverty -
SDG 3 Good Health and Well-being -
SDG 11 Sustainable Cities and Communities
Fingerprint
- 1 Similar Profiles
Collaborations and top research areas from the last five years
-
A two-stage joint modeling approach for multiple longitudinal markers and time-to-event data
Baghfalaki, T., Hashemi, R., Helmer, C. & Jacqmin-Gadda, H., 12 Jan 2026, (E-pub ahead of print) In: Statistical Methods in Medical Research.Research output: Contribution to journal › Article › peer-review
-
Joint modeling of mixed skewed longitudinal responses using convolution of normal and log-normal distributions: a Bayesian approach
Malekpour, R., Baghfalaki, T., Ganjali, M. & Pourdarvish, A., 2 Jan 2026, In: Communications in Statistics: Simulation and Computation. 55, 1, p. 221-243 23 p.Research output: Contribution to journal › Article › peer-review
-
A Bayesian joint bent-cable model for longitudinal measurements and survival time with heterogeneous random-effects distributions
Ariyo, O., Olobatuyi, K. & Baghfalaki, T., 20 Jan 2025, In: Journal of Biopharmaceutical Statistics. 14 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Advantages of Certain Bayes Estimators as Preferred Alternatives to Frequentist Methods
Ganjali, M. & Baghfalaki, T., Aug 2025, In: Sankhya. Series A: mathematical statistics and probability . 87, 2, p. 616-642 27 p.Research output: Contribution to journal › Article › peer-review
-
Approximate Bayesian inference for joint partially linear modeling of longitudinal measurements and spatial time-to-event data
Baghfalaki, T., Ganjali, M. & Martins, R., 2 Nov 2025, In: Journal of Statistical Computation and Simulation. 95, 16, p. 3548-3576 29 p.Research output: Contribution to journal › Article › peer-review