Statistical Concepts for Medical Writers: A Beginner's Guide

In this lecture, you will understand the differences between intent-to-treat, per-protocol, safety-evaluable and worst-case. The above concepts will be explained by using a numerical example.

In this lecture, you will understand the use of responder rates in an intent-to-treat analysis (ITT) compared with a per-protocol analysis (PPA). Students will find an answer to some of their questions. Are you ready?

By using plausible data you will have to choose which responder rate should be used and you will also have to explain why.

You are not alone in this journey, here is the solution to the essay. You can compare it with your essay.

There are no secrets just train your amazing writing skills! 

That's the only thing to do! Congratulations you are doing a great job!

As a medical writer or health writer, you will probably need to communicate statistical results or statistical data to doctors and physicians, here is how to do it.

Your public will always be interested in better understanding statistical data, as clinical data can be appealing only if they are plainly clarified. This exercise will put you on the right track to do it.

Talking to young students is not always simple, in particular, if you have to report statistical concepts but here you will find the tools to do it.

Intent-to-treat, per-protocol, worst-case and safety-evaluable analyses are of course not enough to understand a clinical trial! The above exercises were created to let you train your writing skills. I hope you enjoyed them. In the next lessons, we will combine the necessary statistical concepts to move forward.

Hi and welcome to the lesson sensitivity analyses in clinical trials!

In this lesson, you will find a practical example of sensitivity analysis in a clinical trial to evaluate the efficacy of a new medication for treating high blood pressure.

In this article “A tutorial on sensitivity analysis in clinical trials: the what, why, when and how” the different types of sensitivity analyses are introduced.

What do you, as a medical writer, think might be useful to have clear in mind for reporting clinical data?

Measures such as the mean, median, and mode give an idea of the central tendency of a data set, meanwhile, the range and percentiles give an idea of the spread of the data. In this lesson, practical examples will help you to understand them better.

This lesson introduces the following concept:

• Estimate (a value that is calculated from the sample data to approximate a population parameter)

• Confidence interval (a range of values that is likely to contain the true population parameter with a certain level of confidence)

• Probability (a measure of the likelihood of an event occurring)

• Standard deviation (a measure of the spread of a data set).

• Standard error of the mean (a measure of the variability of the sample mean)

• P-value (used in hypothesis testing to determine the probability of obtaining a sample statistic as extreme or more extreme than the one observed, assuming that the null hypothesis is true)

  
  

  I would like to draw your attention to the topic of standard deviation covered in our course. You will notice that there are two definitions provided for standard deviation, both of which are correct. However, one is slightly more complex than the other.

  To enhance your understanding of this crucial concept, I have added a clear and concise explanation of standard deviation along with a practical example. This explanation aims to simplify the concept and illustrate its application in real-world scenarios.

  You can find this updated explanation in the relevant section on the course platform. I encourage you to review it carefully to solidify your understanding of standard deviation and its importance in statistical analysis.

By the end of this lesson, you should have a better understanding of how confidence intervals can help you make more informed decisions.

As you will probably need to communicate with doctors and physicians, this lesson will help you to do so. A new exercise for calculating the p-value has been added to the course materials. This exercise is designed to reinforce your understanding of hypothesis testing and statistical significance.

Take your time to work through the questions and apply the concepts you've learned in the lessons. Remember to use the appropriate formulas and techniques to arrive at your answers.

In the next lesson, you will find the solution to this exercise. I encourage you to attempt the exercise before reviewing the solution.

In this lesson, you will be able to create your summary of guidelines for statistical reporting in medical

journals. Here you will find the solution to the exercise on calculating the p-value. The solution has been carefully crafted to provide a clear explanation of each step in the process, allowing you to deepen your understanding of hypothesis testing and statistical analysis.

You can access the solution in the designated section on the course platform. Take your time to review the solution and compare it with your own answers from the exercise. Pay close attention to the reasoning behind each calculation and consider any discrepancies between your approach and the solution provided.

In this lesson, typical misinterpretations of statistical tests, p-values, confidence intervals, and power are explained and you will find the way to discover them.

In this session, I take advantage of sample size calculation to let you do an exercise that implies the ability to summarise data and parameters.

This lesson clarifies the difference between statistical and clinical significance.

Slide deck is the term used in medical writing for a PowerPoint presentation or with other supports that imply the preparation of slides. Among the selection tests for a medical writer, there may also be the preparation of a slide deck, for this reason, I invite you to work seriously on your presentation. Good luck!

Welcome to the conclusion of this course about reporting basic statistical concepts in clinical trials.

Now you have a comprehensive introduction to the world of statistics for medical and health writers.

I am pleased to inform you that I have added a glossary containing the key terms covered in the course. This glossary serves as a valuable resource for quick reference and clarification of any terminology you may encounter throughout the course.

Each term is accompanied by a concise definition to aid in your understanding. I highly recommend utilizing this resource to reinforce your comprehension of the material.

Thank you for taking "Statistical Concepts for Medical Writers: A Beginner's Guide".