Real-world data are fundamental to modern teaching methodologies that aim to improve statistical knowledge and reasoning in students. Statistical information is encountered in everyday life, such as media articles and involves real-world contexts. However, information could be biased or (mis)represented and students should be concerned about the…

During the COVID-19 pandemic, a group of health program implementors and research analysts across seven low- and middle-income countries (LMICs) alongside Boston-based collaborators convened to implement data-driven approaches for public health response. An intensive statistics and data science training short course was developed to ensure that…

Selection of appropriate study design and analytical methods is critical for producing robust research, as the design and analytical approach used can ultimately shape results and their interpretation. The objective of this research was to examine how findings from a large repeat cross-sectional data system compare to those from a sample of…

Political communication exemplifies rhetoric and propagandist approach in its various forms, among which the Aristotle's rhetorical theory and its three aspects, ethos, pathos and logos are the major ones. This study used these three as indicators of public rhetoric in the context of Indonesian parliamentarian speeches This study used a…

Background: We conducted a rapid scoping review to identify how inclusive research teams use technology during the research process that could support remote collaboration during public health emergencies like the COVID-19 pandemic. Method: We searched three databases and conducted a hand search. Two independent reviewers screened 1498 abstracts…

This book prepares and guides individuals who are about to embark (or already have embarked) on a health/medical PhD journey, with a specific focus on Public Health. Based on the author's experience as a recently graduated Doctor of Philosophy (PhD) student, readers benefit from the knowledge imparted and lessons learned, including an analysis of…

Agent-based models combine data and theory during both development and use of the model. As models have become increasingly data driven, it is easy to start thinking of agent-based modelling as an empirical method, akin to statistical modelling, and reduce the role of theory. We argue that both types of information are important where the past is…