1st Edition
Applied Biostatistical Principles and Concepts Clinicians' Guide to Data Analysis and Interpretation
Part I. Design Process
Chapter One Basics of Biomedical and Clinical Research
Chapter Two Research Design: Experimental & Non-experimental Design
Chapter Three Population, Sample, ,Biostatistical Reasoning & Probability
Part II. Biostatistical Modeling
Chapter Four Statistical Consideration in Clinical Research
Chapter Five Sample Size and Power Estimations
Chapter Six Single Sample Statistical Inference
Chapter Seven Two Independent Samples Statistical Inference
Chapter Eight Statistical Inference in Three or More Samples
Chapter Nine Statistical Inference Involving Relationships
Chapter Ten Special Topics in Modern Evidence Discovery
Biography
Laurens Holmes Jr. was trained in internal medicine, specializing in immunology and infectious diseases prior to his expertise in epidemiology (cancer)-with- biostatistics (survival analysis). Over the past two decades, Dr. Holmes had been working in cancer epidemiology, control & prevention. His involvement in biostatistical modeling of health research data includes signal amplification and stratification in risk modelling, evidence discovery through effect size and confidence interval (not p value) and evidence-based clinical and translational research through Quantitative Evidence Synthesis (QES).
