Spotlight: Congratulations to Halima Twabi on her recent publication, co-authored with Prof. Samuel Manda
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Their work, titled "Methods Using Propensity Scores to Estimate Causal Effects in Observational Longitudinal Studies," explores innovative statistical methods to strengthen causal inference in complex health data.
Using real-world data from the 2010 and 2015–2016 Malawi Demographic Health Surveys, they applied and extended propensity score methods including PSM, IPTW, and subclassification to address time-varying exposures, multivariate outcomes, and confounding in longitudinal studies.
Key findings include:
- Maternal HIV is associated with lower birth weight and higher perinatal death rates.
- Subclassification and IPTW approaches can yield different causal estimates, showing the importance of method selection.
- A bivariate MSM-IPTW model showed smaller effects of HIV awareness on condom use and multiple sexual partners than univariate models.
A significant contribution to advancing methods in observational research and public health policy!
Methods Using Propensity Scores to Estimate Causal Effects in Observational Longitudinal Studies | SpringerLink