The past three decades have witnessed modern advances in
statistical modeling and evidence discovery in biomedical,
clinical, and population-based research. With these advances come
the challenges in accurate model stipulation and application of
models in scientific evidence discovery Applied Biostatistical
Principles and Concepts provides practical knowledge using
biological and biochemical specimen/samples in order to understand
health and disease processes at cellular, clinical, and population
levels. Concepts and techniques provided will help researchers
design and conduct studies, then translate data from bench to
clinics in attempt to improve the health of patients and
populations. This book is suitable for both clinicians and health
or biological sciences students. It presents the reality in
statistical modelling of health research data in a concise manner
that will address the issue of "big data" type I error tolerance
and probability value, effect size and confidence interval for
precision, effect measure modification and interaction as well as
confounders, thus allowing for more valid inferences and yielding
results that are more reliable, valid and accurate.
General
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