Understanding Clinical Research: Behind the Statistics

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About this course: 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…

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When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

About this course: 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.

Created by:  University of Cape Town
  • Taught by:  Juan H Klopper, Dr

    Department of Surgery
Commitment 6 weeks of study, 2-3 hours/week Language English How To Pass Pass all graded assignments to complete the course. User Ratings 4.7 stars Average User Rating 4.7See what learners said Coursework

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University of Cape Town The University of Cape Town is the oldest university in South Africa and is one of the leading research universities on the African continent. UCT has over 25 000 students, of whom 30% are postgraduate students. We offer degrees in six faculties: Commerce, Engineering & the Built Environment, Health Sciences, Humanities, Law, and Science. We pride ourself on our diverse student body, which reflects the many cultures and backgrounds of the region. We welcome international students and are currently home to thousands of international students from over 100 countries. UCT has a tradition of academic excellence that is respected world-wide and is privileged to have more than 30 A-rated researchers on our staff, all of whom are recognised as world leaders in their field. Our aim is to ensure that our research contributes to the public good through sharing knowledge for the benefit of society. Past students include five Nobel Laureates – Max Theiler, Alan Cormack, Sir Aaron Klug, Ralph Bunche and, most recently, J M Coetzee.

Syllabus


WEEK 1


Getting things started by defining study types



Welcome to the first week of this course. We’ll be tackling five broad topics to provide you with an intuitive understanding of clinical research results. This isn’t a comprehensive statistics course, but it offers a practical orientation to the field of medical research and commonly used statistical analysis. The first topics will look at research methods and the collection of data - with a specific focus on study types. By the end of the lectures you should be able to identify which study types are being used and why the researchers selected them when you are reading a paper.


11 videos, 11 readings, 1 practice quiz expand


  1. Video: Introduction to Understanding Clinical Research
  2. Video: About the course
  3. Reading: How this course works
  4. Reading: Pre-course survey
  5. Discussion Prompt: Introduce yourself to your peers
  6. Reading: Study types
  7. Video: Observing and intervening: Observational & experimental studies
  8. Reading: Key notes: Observational and experimental studies
  9. Video: Observing and describing: Case series studies
  10. Reading: Key notes: Case series studies
  11. Video: Comparing groups: Case-control studies
  12. Reading: Key notes: Case-control studies
  13. Video: Collecting data at one point in time: Cross-sectional studies
  14. Reading: Key notes: Cross-sectional studies
  15. Video: Studying a group with common traits: Cohort studies
  16. Reading: Key notes: Cohort studies
  17. Video: Let's intervene: Experimental studies
  18. Reading: Key notes: Experimental studies
  19. Video: Working with existing research: Meta-analysis and Systematic Review
  20. Reading: Key notes: Meta-analysis and systematic review
  21. Practice Quiz: Test your knowledge: Study types
  22. Reading: Peer review introduction
  23. Video: Doing a literature search: Part 1
  24. Video: Doing a literature search: Part 2

Graded: Week 1: Navigating Clinical Research

WEEK 2


Describing your data



With the next topics, 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. In this week, I am going to tackle the differences in data which determine what type of statistical test we can use in making sense of our data.


15 videos, 12 readings, 3 practice quizzes expand


  1. Video: Introduction
  2. Video: Some key concepts: Definitions
  3. Reading: Key notes: Definitions
  4. Video: Data types
  5. Reading: Key notes: Data types
  6. Video: Arbitary classification: Nominal categorical data
  7. Reading: Key notes: Nominal categorical data
  8. Video: Natural ordering of attributes: Ordinal categorical data
  9. Reading: Key notes: Ordinal categorical data
  10. Video: Measurements and numbers: Numerical data types
  11. Reading: Key notes: Numerical data types
  12. Video: How to tell the difference: Discrete and continuous variables
  13. Reading: Key notes: Discrete and continuous variables
  14. Practice Quiz: Test your knowledge: Data types
  15. Video: Introduction
  16. Reading: Key notes: Describing the data
  17. Video: Measures of central tendency
  18. Reading: Key notes: Measures of central tendency
  19. Video: Measures of dispersion
  20. Reading: Key notes: Measures of dispersion
  21. Reading: Visual representation of data
  22. Video: (Optional) Setting up spreadsheet software to do your own analysis
  23. Video: (Optional) Descriptive statistics using spreadsheet software
  24. Practice Quiz: Test your knowledge: Measures of central tendency and dispersion
  25. Video: Making inferences: Sampling
  26. Reading: Key notes: Sampling
  27. Video: Types of sampling
  28. Reading: Key notes: Types of sampling
  29. Practice Quiz: Test your knowledge: Sampling
  30. Video: Case study 1
  31. Discussion Prompt: Share an example of clinical research

Graded: Week 2 Graded Quiz

WEEK 3


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.


14 videos, 12 readings, 3 practice quizzes expand


  1. Video: P-values: P is for probability
  2. Reading: Key notes: P-values
  3. Video: Working out the probability: Rolling dice
  4. Reading: Key notes: Rolling dice
  5. Video: Area under the curve: Continuous data types
  6. Reading: Key notes: Continuous data types
  7. Practice Quiz: Test your knowledge: Probability
  8. Video: Introduction to the central limit theorem: The heart of probability theory
  9. Reading: Introduction to the central limit theorem
  10. Video: Asymmetry and peakedness: Skewness and Kurtosis
  11. Reading: Key notes: Skewness and kurtosis
  12. Video: Learning from the lotto: Combinations
  13. Reading: Key notes: Combinations
  14. Video: Approximating a bell-shaped curve: The central limit theorem
  15. Reading: Key notes: Central limit theorem
  16. Practice Quiz: Test your knowledge: The central limit theorem
  17. Video: Patterns in the data: Distributions
  18. Reading: Key notes: Distributions
  19. Video: The bell-shaped curve: Normal distribution
  20. Reading: Key notes: Normal distribution
  21. Video: Plotting a sample statistic: Sampling distribution
  22. Reading: Key notes: Sampling distribution
  23. Video: Standard normal distribution: Z distribution
  24. Reading: Key notes: Z-distribution
  25. Video: Estimating population parameters: t-distribution
  26. Reading: Key notes: The t-distibution
  27. Video: (Optional) Generating random data point values using spreadsheet software
  28. Practice Quiz: Test your knowledge: Distributions
  29. Video: Case study 2

Graded: Week 3 Graded Quiz

WEEK 4


The important first steps: Hypothesis testing and confidence levels



In general, a researcher has a question in mind that he or she needs an answer to. Everyone might have an opinion on the question (or answer), but an investigator looks for the answer by designing an experiment and investigating the outcome. In the first lesson 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.


8 videos, 6 readings, 2 practice quizzes expand


  1. Video: Introduction to Hypothesis Testing
  2. Video: Testing assumptions: Null and alternative hypothesis
  3. Reading: Key notes: Null and alternative hypothesis
  4. Video: Is there a difference?: Alternative Hypothesis
  5. Reading: Key notes: Alternative hypothesis
  6. Video: Type I and II: Hypothesis testing errors
  7. Reading: Key notes: Hypothesis errors
  8. Practice Quiz: Testing your knowledge: Hypothesis
  9. Video: Introduction to confidence intervals
  10. Reading: Key notes: Introduction to confidence intervals
  11. Video: How confident are you?: Confidence levels
  12. Reading: Key notes: Confidence levels
  13. Video: Interval estimation: Confidence intervals
  14. Reading: Key notes: Confidence intervals
  15. Video: (Optional) Calculating confidence intervals using spreadsheet software
  16. Practice Quiz: Test your knowledge: Confidence intervals

Graded: Week 4 Peer review

WEEK 5


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.


15 videos, 6 readings, 2 practice quizzes expand


  1. Video: Introduction to parametric tests
  2. Reading: Key notes: Parametric tests
  3. Video: Student's t-test
  4. Reading: Key notes: Student's t-test
  5. Video: ANOVA
  6. Reading: Key notes: ANOVA
  7. Video: Linear Regression
  8. Reading: Key notes: Linear regression
  9. Video: (Optional) Student's t-test in action
  10. Practice Quiz: Test your knowledge: Parametric tests
  11. Video: Introduction to nonparametric tests
  12. Video: Checking for normality
  13. Reading: Key notes: Nonparametric tests
  14. Video: Thinking nonparametrically
  15. Video: Comparing paired observations: Signs
  16. Video: Ordering values: Ranking
  17. Video: Paired comparisons: Sign ranks
  18. Video: Summation of ranks: Rank sums
  19. Video: Comparing two populations: Mann-Whitney-U test
  20. Video: nonparametric tests
  21. Reading: Key notes: Nonparametric tests
  22. Practice Quiz: Test your knowledge: Non-parametric tests
  23. Video: Case study 3

Graded: Week 5 Graded Quiz

WEEK 6


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.


8 videos, 4 readings, 2 practice quizzes expand


  1. Video: Introduction to comparing categorical data
  2. Video: Observed frequencies: Contingency tables
  3. Video: Comparing observed and expected values: Chi-square test
  4. Video: Association between two variables: Fisher's exact test
  5. Reading: Key notes: Comparing categorical data
  6. Video: (Optional) Calculating chi-square test using spreadsheet software
  7. Practice Quiz: Testing your knowledge: Comparing categorical data
  8. Video: Introduction to sensitivity and specificity
  9. Video: Measuring performance: Sensitivity and specificity
  10. Video: Proportions of results: Positive and negative predictive values
  11. Reading: Keynotes: Sensitivity, specificity, positive and negative predictive values
  12. Practice Quiz: Test your knowledge: Sensitivity, specificity and predictive values
  13. Reading: Interesting online videos
  14. Reading: Congratulations on completing the course

Graded: Week 6 Final examination

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