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Causal Inference in Pharmaceutical Statistics introduces the basic concepts and fundamental methods of causal inference relevant to pharmaceutical statistics. This book covers …
Cell and gene therapies have become the third major drug modality in pharmaceutical medicine of the 21st century after low molecular weight and antibody drugs. The gene therapy …
Bayesian Precision Medicine presents modern Bayesian statistical models and methods for identifying treatments tailored to individual patients using their prognostic variables and …
Value of Information for Healthcare Decision-Making introduces the concept of Value of Information (VOI) use in health policy decision-making to determine the sensitivity of …
Confidence Intervals for Discrete Data in Clinical Research is designed as a toolbox for biomedical researchers. Analysis of discrete data is one of the most used yet vexing areas …
Drug development is a strictly regulated area. As such, marketing approval of a new drug depends heavily, if not exclusively, on evidence generated from clinical trials. Drug …
This book covers classic epidemiological designs that use a reference/control group, including case-control, case-cohort, nested case-control and variations of these designs, such …
This book begins with an introduction of pragmatic cluster randomized trials (PCTs) and reviews various pragmatic issues that need to be addressed by statisticians at the design …
A disease is defined as rare if the prevalence is fewer than 200,000 in the United States. It is estimated that there are more than 7,000 rare diseases, which collectively affect …
Useful Statistical Approaches for Addressing Multiplicity IssuesIncludes practical examples from recent trials Bringing together leading statisticians, scientists, and clinicians …