Day 3: Wednesday 10 June

STATISTICAL METHODS FOR DIAGNOSTIC ACCURACY IN MEDICAL RESEARCH

This one-day course is designed for researchers who want to analyse their own diagnostic accuracy data. Typically, this will be analysis on results from research carried out in an early development/exploratory phase but the methods covered will also be applicable to research where tests are studied in a clinical setting. Participants will gain hands-on experience of analysing diagnostic accuracy data in computer practical sessions using the free statistical software R (https://cran.r-project.org/).

Prerequisites.

Participants should have a basic understanding of statistics up to the level of confidence intervals and p-values. A rudimentary knowledge of the basics of diagnostic accuracy would be advantageous, but not required as we will revise the basics in the first session. Participants will be expected to bring their own laptops and have R and/or RStudio installed.

By taking this course:

Participants will increase their understanding of common measures of diagnostic accuracy, learn how to calculate these measures using data and quantify uncertainty in their estimates. They will learn when and how to use ROC analysis, how to compare two diagnostic tests and understand methods for finding optimal thresholds.

Course content in detail

1. Summary estimates of diagnostic accuracy (sensitivity, specificity, predictive values, likelihood ratios and other measures)

2. Receiver operating characteristics (ROC)

3. Comparing the accuracy of two tests (paired and unpaired designs)

4. Methods for finding optimal thresholds (including interpretation of the ROC curve, and net-benefit analysis)