Modern Biostatistical Principles and Concepts: Guidelines for Study Analysis, Interpretation & Application

by Laurens Holmes

Overview

This text, Modern Biostatistics for Clinical, Biomedical and Population-Based Researchers has filled this gap, not only in the way complex modeling is explained but the simplification of statistical techniques in a way that had never been explained before. This text has been prepared intentionally at the rudimentary level to benefit clinicians without sophisticated mathematical backgrounds or previous advanced knowledge of biostatics as applied statistics in health and medicine. Also, biomedical researchers who may want to conduct clinical research, as well as consumers of research products may benefit from the sampling techniques, their relevance to scientific evidence discovery as well a simplified approach to statistical modeling of clinical and biomedical research data. It is with this expectation and enthusiasm that we recommend this text to clinicians in all fields of clinical and biomedical research. One's experience with biomedical research and how the findings in this arm are translated to the clinical environment signals the need for the application of biological, and clinical relevance of findings prior to statistical inference. The examples provided by the author to simplify research methods are familiar to orthopedic surgeons as well as clinicians in other specialties of medicine and surgery.

Product Details

ISBN-13:	9798341878211
Publisher:	Barnes & Noble Press
Publication date:	01/24/2025
Pages:	448
Product dimensions:	8.50(w) x 11.00(h) x 0.91(d)

About the Author

Dr. Holmes is a strong proponent of Reality in the Statistical Modeling of cancer and experimental as well as non-experimental research data, where he presents the rationale for tabular analysis in non-experimental design research data, which are often not randomly sampled (probability sampling) rendering statistical inference application meaningless to such data, as non-random sampling variables. However, the point estimate, as clinically and biologically meaningful difference remains feasible in specific patient population. Since controlling for known confounders of variables in subgroup health and healthcare outcomes often fails to remove or explain these imbalances, a feasible alternative is to consider subgroup biologic/cellular events/molecular level variances or differences. One of the Biostatistical approaches to address valid inference in population-based, biomedical and clinical research is a model that amplifies signals in the data prior to risk stratification, implying the role of biostatistics as a tool in scientific evidence discovery, had been proposed by Dr. Holmes – “Signal Amplification and Risk Specific Stratification, SARSSm” Professor Holmes is currently the Director of Public Health Program at Delaware State University, Dover, DE-USA, and Distinguished Professor at FAMU, Institute of Public Health, Tallahassee, FL., USA