Causal Modeling Helps Machine Learning Find Better Drug Targets
In the rapidly advancing field of drug discovery, artificial intelligence and machine learning are revolutionizing how researchers identify potential therapeutic targets. While traditional predictive models ...
Read More →
Best Causal Inference Books | The Full List
The collection of works on causal inference and research design presents a comprehensive spectrum of approaches, methodologies, and applications across various fields, including epidemiology, economics, ...
Read More →
Biostatistics in Public Health: Principles, Methods, and Case-Studies – A Comprehensive Guide
Biostatistics plays a crucial role in public health by providing the statistical foundation for analyzing health data, designing studies, and guiding evidence-based decisions. From tracking ...
Read More →
The Battle For The Soul Of Causal Inference
Explore the decades-long intellectual rivalry shaping how we understand causality in data science. This analysis examines the fundamental tension between two giants of causal methodology: ...
Read More →
Association Does Not Imply Causation, Except When it Does – A Causal Inference Perspective
Delving into the critical distinction between correlation and causation, this article explores why establishing true causal relationships remains one of the most challenging aspects of ...
Read More →
Selection Bias, A Causal Inference Perspective (With Downloadable Code Notebook)
Collider bias occurs when we condition on (or select based on) a variable that is influenced by both the exposure and outcome of interest. This ...
Read More →
