Practical session at a 'Lung Function Testing in the Workplace - Introductory Level' course

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Date tbc: Introductory Medical Statistics - one- or two-day course

Category: statistical

13 May, 2021

Generic photo of laptop, to illustrate this course ('Introductory Medical Statistics' - probably May 2021 - date tbc)

Thursday 13 and/or Friday 14 May 2021 are likely dates (tbc): one or two days

(virtual or in 'person')

Contact Magda Wheatley for further information.

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Registration fees tbc.  


Course description (as of our November 2020 course; possibly to be revised for May 2021).

November 2020 was held 'virtually' on Microsoft Teams -

* see an image of a session in action here (courtesy of James Potts) *

Designed to introduce anyone who uses statistics in their work or research to the following:

- Basic epidemiological concepts (hierarchy of evidence and differences in study designs;confounding in observational studies vs. RCTs
- Descriptive statistics for quantitative, ordinal and qualitative data (mean, median and mode; standard deviation, percentiles and frequency distribution)
- Inferential statistics: estimating parameters in the population (confidence intervals)
- Testing a hypothesis (p-values; choosing a test; types of errors – false positive and false negative results; multiple testing)
- Correlation vs. simple linear regression to test relationships between quantitative variables (differences in aims and links between the two approaches; simple linear regression vs. ANOVA)
- Multiple linear regression to adjust for confounding; Interpretation of findings; examples of the impact of confounding on estimates of interest
- Different measures of risk (binary outcomes): relative measures of risk (odds ratio, relative risk, hazard ratio); absolute measures of risk (risk difference, NNT/NNH)
- Simple and multiple logistic regression (binary outcomes): interpretation of findings; examples of the impact of confounding on the estimates of interest
- Power and sample size calculations: why we need them and what parameters we need to perform them ; examples of sample size and power calculations for continuous and binary outcomes

The course will conclude with a practical session: revision and discussion of concepts presented in the course using real examples. Feedback with answers to questions through online voting.

Suitable for - Doctors, nurses, clinical research fellows and postgraduate students

Accreditation by the Royal College of Physicians will be sought

Feedback from our two-day, face-to-face course, November 2019 (Nov 2020 feedback will be added in due course): 

"Absolutely great course!  All speakers were good and helpful."

"All presentations excellent. Very good speakers; concepts explained very clearly."

"Enjoyed the course a lot.  Very well prepared and presented."

"Excellent course – I will recommend to colleagues."

"Handout materials all very comprehensive and easy to understand. The booklet will be a very useful reference."

"The handout is arranged in a well-organised order. It is easy to follow the chapters taught."

"The practical was a great way of reinforcing concepts from the lectures! Really liked this/found it helpful!"

"Very helpful study days – thank you."


Credit for main photo: Carlos Muza on Unsplash 

A few 'in person' photos from November 2019 (credits: Diana van der Plaat): 

James Potts introduces the first of his two practical Data Analysis sessions; Alex Adamson presents 'Power and sample size'; Winston Banya presents 'Basic concepts of survival analysis'; the paper critique session in progess.