Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Biostatistics with Python

You're reading from   Biostatistics with Python Apply Python for biostatistics with hands-on biomedical and biotechnology projects

Arrow left icon
Product type Paperback
Published in Nov 2024
Publisher Packt
ISBN-13 9781837630967
Length 374 pages
Edition 1st Edition
Languages
Concepts
Arrow right icon
Author (1):
Arrow left icon
Darko Medin Darko Medin
Author Profile Icon Darko Medin
Darko Medin
Arrow right icon
View More author details
Toc

Table of Contents (24) Chapters Close

Preface 1. Part 1:Introduction to Biostatistics and Getting Started with Python
2. Chapter 1: Introduction to Biostatistics FREE CHAPTER 3. Chapter 2: Getting Started with Python for Biostatistics 4. Chapter 3: Exercise 1 – Cleaning and Describing Data Using Python 5. Chapter 4: Part 1 Exemplar Project – Load, Clean, and Describe Diabetes Data in Python 6. Part 2:Introduction to Python for Biostatistics – Methodology and Examples
7. Chapter 5: Introduction to Python for Biostatistics 8. Chapter 6: Biostatistical Inference Using Hypothesis Tests and Effect Sizes 9. Chapter 7: Predictive Biostatistics Using Python 10. Chapter 8: Part 2 Exercise – T-Test, ANOVA, and Linear and Logistic Regression 11. Chapter 9: Biostatistical Inference and Predictive Analytics Using Cardiovascular Study Data 12. Part 3:Clinical Study Design, Analysis, and Synthesizing Evidence
13. Chapter 10: Clinical Study Design 14. Chapter 11: Survival Analysis in Biomedical Research 15. Chapter 12: Meta-Analysis – Synthesizing Evidence from Multiple Studies 16. Chapter 13: Survival Predictive Analysis and Meta-Analysis Practice 17. Chapter 14: Part 3 Exemplar Project – Meta-Analysis of Survival Data in Clinical Research 18. Part 4:Biological and Statistical Variables and Frameworks, and a Final Practical Project from the Field of Biology
19. Chapter 15: Understanding Biological Variables 20. Chapter 16: Data Analysis Frameworks and Performance for Life Sciences Research 21. Chapter 17: Part 4 Exercise – Performing Statistics for Biology Studies in Python 22. Index 23. Other Books You May Enjoy

Learning about the principles of clinical trials

Clinical trials are designed to address many of the problems we have in observational studies and provide medicine with the most trustworthy results possible. For this reason, clinical trials are designed as more or less controlled experiments.

Clinical trials have a specific primary outcome or outcomes of interest to evaluate. These outcomes are related to the main goal of the study. Some examples can be the safety or efficacy of the drug, side effects, or other specific clinical outcomes, such as the survival of patients, which are still in a way related to the efficacy of drugs.

There are four types of clinical trials—Phase I, Phase II, Phase III, and Phase IV. All these trials are part of the drug discovery and research pipeline and are closely connected to each other. While the initial phases are meant to mainly evaluate the drug safety profile, later phases, especially after Phase III, are mostly focused on the efficacy...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image