Glossary - Research Basics and Terminology

• Aspect of a subject’s condition, lifestyle or environment that affects the probability of a disease to occur 
• Example: obesity = risk factor for high blood pressure

• Measure of a test’s ability to correctly detect people with the disease
• Sensitivity and specificity are inversely proportional: when sensitivity increases, specificity decreases and vice versa
• Example: 

Further information:  Understanding and using sensitivity, specificity and predictive values.

Example for using sensitivity in a study:  Sensitivity and specificity of mammography and adjunctive ultrasonography to screen for breast cancer in the Japan Strategic Anti-cancer Randomized Trial (J-START): a randomised controlled trial. 

• Asymmetrical shape of distribution
  
• Types

• Measure of a test’s ability to correctly identify people who do not have the disease
• Sensitivity and specificity are inversely proportional: when sensitivity increases, specificity decreases and vice versa
• Example: 

Further information:  Understanding and using sensitivity, specificity and predictive values

• Result that is unlikely to have happened by chance
• It is assessed by the p-value

• Incorrectly rejecting the null hypothesis
• Concluding that there is a relationship when no relationship exists
• Example: if α=0.01, then there is a 1% chance for an α-error
• False Positive

• Incorrectly accepting the null hypothesis
• Concluding no relationship exists even though a relationship does exist
• False Negative

• Degree to which a result is likely to be true and free of bias
• Test is measuring what is needed
• Accuracy of a test
• Example:

Further information: Understanding and using sensitivity, specificity and predictive values