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Statistics in clinical trials. Part 3
Rating: 3.0 out of 5(4 ratings)
29 students

Statistics in clinical trials. Part 3

Statistics, biostatistics, clinical trials, data analysis in medicine.
Created byBioStat Statistics
Last updated 9/2023
English

What you'll learn

  • You will deepen your understanding of statistics and its practical use in clinical research.
  • You will master key survival analysis methods used in clinical trials.
  • You will learn to build and interpret regression models with mixed effects.
  • You will gain the skills to independently estimate sample sizes for studies.

Course content

1 section • 7 lectures • 39m total length

  • Survival analysis6:16

    The first lesson covers the topic of survival analysis, including concepts such as events and censoring, as well as their relation to regression analysis.

  • Survival analysis models4:40

    In the second lesson, the listener will be introduced to the concept of the Kaplan-Meier estimator, one of the most popular statistical methods used in survival analysis. Additionally, they will learn about the Cox proportional hazards model and how to compare commonly referred to as survival curves.

  • Bioequivalence3:28

    During the third lesson, the listener will learn about the concept of bioequivalence and the associated tests of inferiority and non-inferiority.

  • Mixed effects models3:53

    The fourth lesson is devoted to mixed models and the types of effects found in such models.

  • Cox regression and model selection2:10

    The fifth lesson covers the topic of Cox model and model selection.

  • Sample size estimation problem14:50

    The sixth lesson addresses the issue of sample size estimation.

  • Directions of statistics development clinical trials4:42

    The seventh lesson focuses on the future directions of statistics in clinical research, introducing concepts such as bootstrap, meta-analysis, and machine learning.

Requirements

  • Basic computer literacy with a Windows operating system, familiarity with concepts from the " Statistics in Clinical Trials. Part 1" and " Statistics in Clinical Trials. Part 2" courses.

Description

Who Is This Course For?

Are you working in clinical research or looking to enhance your expertise in medical statistics? If so, this course is for you! Statistics in Clinical Trials – Part 3 is designed for professionals who want to build upon their existing knowledge of statistics and explore advanced methods used in real-world clinical studies.

This course covers the most widely used statistical models in clinical trials, including Kaplan-Meier survival curves, Cox proportional hazards models, and linear mixed-effects models. Additionally, you will learn various approaches for estimating sample sizes—an essential skill for designing robust clinical studies.

We also explore the latest trends in modern clinical research, providing valuable insights into how statistical methods are evolving in the field.

This course is ideal for:

  • Clinical researchers and professionals working with medical data

  • Scientists and academics involved in medical research

  • Statisticians seeking to apply their knowledge to clinical settings

  • Anyone with a basic understanding of statistics who wants to deepen their expertise in clinical trial analysis

If you have a background in statistics and are eager to see its practical applications in medicine, this course will give you the tools to analyze and interpret clinical data effectively.


What Will You Learn?

By the end of this course, you will:

  • Master survival analysis techniques, including Kaplan-Meier curves and Cox regression models

  • Understand and apply linear mixed-effects models in clinical research

  • Learn how to perform equivalence testing and interpret results in a medical context

  • Develop the skills to calculate sample sizes for various types of clinical trials

  • Gain insights into emerging trends and statistical challenges in modern clinical research.

This course bridges the gap between theoretical knowledge and real-world applications, providing hands-on insights into the statistical models that drive clinical decision-making.

Who this course is for:

  • Employees in the clinical research industry, in positions such as clinical trial assistant (CTA), clinical research associate (CRA), project manager and others related to clinical research practice.
  • Doctors whose medical and scientific activities are related to clinical research
  • Academics who use statistical analysis in their research
  • Students who need basic knowledge of statistics.

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