Randomization, blinding and controls: the design choices that make causal claims possible
Statistics can quantify uncertainty, but it cannot manufacture a fair comparison after a badly designed experiment. Randomization, masking and controls.
Aomics · Insights
Practical articles on adaptive clinical trials, biostatistics, RBQM, statistical programming and AI in clinical research — by Dr. Sakshi Bharti and the Aomics team.
Statistics can quantify uncertainty, but it cannot manufacture a fair comparison after a badly designed experiment. Randomization, masking and controls.
Endpoints in Clinical Trials: Continuous, Binary, Count and Time-to-Event. Practical guidance for clinical-trial statisticians, programmers and...
A primary endpoint is not automatically the same thing as the treatment effect you want to estimate. That distinction is central to modern clinical.
Clinical research is document-heavy because different documents control different parts of the study. Knowing their boundaries prevents downstream.
Reading a Clinical Trial Protocol Like a Statistician. Practical guidance for clinical-trial statisticians, programmers and adaptive-design teams.
One of the fastest ways to become useful in clinical research is to understand who owns which decision. Many analytical mistakes begin as ownership.
How a Medicine Moves from Discovery to Approval—and Where Statistics Enters. Practical guidance for clinical-trial statisticians, programmers and...
Phase I, II, III and IV sound like a simple sequence, but the statistical objective changes substantially. The useful question is: what decision is this.
What Does a Clinical Trial Statistician Actually Do?. Practical guidance for clinical-trial statisticians, programmers and adaptive-design teams.
A statistician can understand regression and still feel lost in a clinical-study meeting. Clinical research has its own language, roles, documents and.