Understanding Clinical Research: Behind the Statistics
University of Cape Town via Coursera
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Overview
If you’ve ever skipped over the results section of a medical paper because terms like “confidence interval” or “p-value” go over your head, then you’re in the right place. You may be a clinical practitioner reading research articles to keep up-to-date with developments in your field or a medical student wondering how to approach your own research. Greater confidence in understanding statistical analysis and the results can benefit both working professionals and those undertaking research themselves.
If you are simply interested in properly understanding the published literature or if you are embarking on conducting your own research, this course is your first step. It offers an easy entry into interpreting common statistical concepts without getting into nitty-gritty mathematical formulae. To be able to interpret and understand these concepts is the best way to start your journey into the world of clinical literature. That’s where this course comes in - so let’s get started!
The course is free to enroll and take. You will be offered the option of purchasing a certificate of completion which you become eligible for, if you successfully complete the course requirements. This can be an excellent way of staying motivated! Financial Aid is also available.
Syllabus
- Getting things started by defining study types
- Welcome to the first week. Here we’ll provide an intuitive understanding of clinical research results. So this isn’t a comprehensive statistics course - rather it offers a practical orientation to the field of medical research and commonly used statistical analysis. The first topics we will look at are research methods and data collection with a specific focus on study types. By the end, you should be able to identify which study types are being used and why the researchers selected them, when you are later reading a published paper.
- Describing your data
- We finally get started with the statistics. Have you ever looked at the methods and results section of any healthcare research publication and noted the variety of statistical tests used? You would have come across terms like t-test, Mann-Whitney-U test, Wilcoxon test, Fisher’s exact test, and the ubiquitous chi-squared test. Why so many tests you might wonder? It’s all about types of data. This week I am going to tackle the differences in data that determine what type of statistical test we can use in making sense of our data.
- Building an intuitive understanding of statistical analysis
- There is hardly any healthcare professional who is unfamiliar with the p-value. It is usually understood to have a watershed value of 0.05. If a research question is evaluated through the collection of data points and statistical analysis reveals a value less that 0.05, we accept this a proof that some significant difference was found, at least statistically.In reality things are a bit more complicated than that. The literature is currently full of questions about the ubiquitous p-vale and why it is not the panacea many of us have used it as. During this week you will develop an intuitive understanding of concept of a p-value. From there, I'll move on to the heart of probability theory, the Central Limit Theorem and data distribution.
- The important first steps: Hypothesis testing and confidence levels
- In general, a researcher has a question in mind that he or she needs to answer. Everyone might have an opinion on this question (or answer), but a researcher looks for the answer by designing an experiment and investigating the outcome. First, we will look at hypotheses and how they relate to ethical and unbiased research and reporting. We'll also tackle confidence intervals which I believe are one of the least understood and often misrepresented values in healthcare research. The most common tests used in the literature to compare numerical data point values are t-tests, analysis of variance, and linear regression. In the last lesson we take a closer look at these tests, but perhaps more importantly, their strict assumptions.
- Which test should you use?
- The most common statistical test that you might come across in the literature is the t-test. There are, in actual fact, a few t-tests, but the one most are familiar with, is of course, Student’s t-test and its ubiquitous p-value. Not everyone, though, knows that the name Student was actually a pseudonym, used by William Gosset (1876 - 1937). Parametric tests have very strict assumptions that must be met before their use is justified. In this lesson we take a closer look at these tests, but perhaps more importantly, their strict assumptions. Once you know these, you will be able to identify when these tests are used inappropriately.
- Categorical data and analyzing accuracy of results
- Congratulations! You've reached the final week of the course Understanding Clinical Research. In this lesson we will take a look at how good tests are at picking up the presence or absence of disease, helping us choose appropriate tests, and how to interpret positive and negative results. We’ll decipher sensitivity, specificity, positive and negative predictive values. You'll end of this course with a final exam, to test the knowledge and application you've learned in this course. I hope you've enjoyed this course and it helps your understanding of clinical research.
Taught by
Dr Juan H Klopper
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Reviews
4.9 rating, based on 851 Class Central reviews
4.8 rating at Coursera based on 3556 ratings
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Overall good, but the course lacks practical examples like demos. E.g how to create dummy data for t-distribution using spread sheet software. Require more examples on nonparametric tests. I feel nonparametric tests are not explained properly. For example, rank sum doesn't make complete sense The course does not explain shortcomings of p value in larger samples. Lastly, there is no explanation on logistic regression that would have made this course complete. This course is nice overview for someone who wants to have basic understanding of clinical research.
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As someone deeply interested in the intersection of healthcare and statistics, I enrolled in the "Understanding Clinical Research Behind Statistics" course with high expectations. I can confidently say that it not only met but exceeded those expecta…
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I found the curriculum of this course provided an excellent overview of core concepts in statistics as it relates to clinical research. This course is suitable for those who have had some prior exposure to basic concepts but needed a refresher to t…
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good way to start with clinical statistic life. The course could help your life easier and change your attitude about research.
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There was a great deal of information in this course that I found extremely helpful. It provides a great overview of clinical research to help those who don't have much understanding of it as well as those with some prior knowledge to gain a better…
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What a great course! I highly recommend it to anyone who is interested in clinical research and wants to understand how statistics is used in clinical research. I loved all aspects of the course. The lecture videos were short and crisp. Dr. Klopper is very engaging and explained even the hardest concepts really well. The quizzes let you apply what you learn. The peer review assignments are a great way of soliciting and giving feedback. Learning this course has really enriched my statistics knowledge.
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I would like to send the most sincere gratitude to the professor and team of the course "Understanding Clinical Research: Behind the Statistics" with the very interesting and useful content of basic statistics in clinical trials. The course is real…
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The course gave me the confidence to face the career in Clinical Research. It is put together in a way that helps every beginner find a streamlined and systematic flow into the subject and field. The materials are easy to understand and follow.…
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Umderstanding Clinical Research Behind the Statistics is a remarkable series of lectures.They are helpfull in understanding issues like the different kind of data,the selection of the proper statistical tests paramertic or nonparametric, the different type of studies and the selection of the samples.In addition these lectures clarify issues like the p value and the confidence interval that in my oppinion both should be mentioned when a conclusion is drawn about the clinical significance of a research.Finally sensitivity,specificity and predictive values were analyzed and well explained.
Thank you for the experience and for having the chance to follow these series.
Giannis -
Amazing course.If you are a beginner and someone who is interested in research then you must take this course to have the better understanding of the research paper.Don't be scared by the word "statistics" mentioned in the title as it doesn't involve complicated mathematics.They have tried to keep is as simple as possible.
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I found this course to be very ideal for someone with no prior research background. It gives a well summarised overview on most of the important concepts that are crucial in clinical research. It has helped improve my understanding of what goes into research and how to have a better approach at reviewing clinical literature that is available. It is broken down into manageable modules with easy to follow instructions and the objectives are clear. It is a worthwhile course to start one’s clinical research journey.
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I have attempted taking courses or reading books on medical statistics earlier, and every time, I took a few baby steps and then aborted. I was good at maths in school, but hey, twenty years in the medical profession, and the confidence sags. This time, I got a bird's eye view of the entire subject, with sufficient detail where required. This course is comprehensive, without being intimidating, and focuses on an intuitive grasp of the subject. I can say for sure that I am more motivated now than ever before, in conducting clinical research the right way. The foundation stones have been laid. I can now build on this knowledge, without fear of statistics getting in the way.
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This course is an excellent introduction to clinical research and statistical concepts. It effectively breaks down complex topics, making them accessible and easy to understand. The content is well-organized, and the real-world examples help to solidify the concepts. I recommend this course to anyone interested in clinical research and its statistical foundations!
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I'm a total beginner in the field of medical statistics but this course have been just right.
I could understand almost all concepts because the course builds from the bases and iterates the concepts mentioned early in future lectures as well.
Thanks Dr Juan Klopper and all the team for this very fun and very valuable course! -
The course is very user friendly. The content was not too overpowering. The way the content was organized and delivered really helped with the completion. For someone who did Biostatistics many years back, this course really offered me a refresher of the basics behind the statistics used in research.
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Thank you! For me it was very helpfull. I have been away from any science for 20 years after my MD. Coming back is a great challenge since so much as changed. Statistic is almost 30 years ago in my brain. So, this was good, appropriate and challenging at the same time.
I'll keep studying with you.
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I really enjoyed this course. It is very well organised with clear objectives and a level of simplicity allowing a beginner to understand and acquire a very grasp on the subject. The information is presented in short easy to digest sections with reg…
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Great course to revise the basics behind statistical analysis in clinical studies. Lectures are to the point, concise and very clearly explained. Definitely would recommend to anyone struggling to understand the materials and methods and results sections of clinical studies.
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To me it was perfect. An excellent way to revise statistics and understand its basics. It is very pedagogical and easy to follow. I wish it had proceeded to more logistic regressions and survival analyses as well. Thank´s, I have really enjoyed it.
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This course has been incredibly useful as it explains the use of statistics in medical research in a straightforward way. It has increased my knowledge of the statistics used in medical research papers which is extremely useful for my work.