Stats

Question 1

What is the sensitivity of an assay and how is it calculated?

Answer 1

The proportion of positive results correctly identified by a test, calculated as follows:

= True positives / (True positives + False negatives) x 100%

Question 2

What is the specificity of an assay and how is it calculated?

Answer 2

The proportion of negative results correctly identified by a test, calculated as follows:

= True negatives / (True negatives + False positives) x 100%

Question 3

What is the accuracy of an assay and how is it calculated?

Answer 3

How often a test gives the correct result (either positive or negative), calculated as follows:

= True results / (True results + False results) x 100%

Question 4

What is the trueness of an assay?

Answer 4

For quantitative tests, where the result can have any value between two limits, this is a measurement of how close the test result is to the reference value. Any deviation from the reference value indicates a systematic error or bias.

Question 5

What is the precision of an assay?

Answer 5

The degree to which separate measurements differ, which indicates how well a single test result is representative of a number of repeats. Precision can be expressed as the standard deviation of a set of replicate results or as a confidence interval around the mean result.

Question 6

What is the repeatability of an assay?

Answer 6

The closeness of agreement of results obtained when using the same samples under the same test conditions (technicians/analysts, instruments, reagent lots etc.) and repeated over a short period of time.
This essentially represents ‘within-run’ precision.

Question 7

What is the reproducibility of an assay?

Answer 7

The closeness of agreement of results obtained when using the same samples under different test conditions (technicians/analysts, instruments, reagent lots etc.).
This essentially represents ‘between-run’ precision

Question 8

What is the positive predictive value and how is it calculated?

Answer 8

The positive predictive value is a measure of the chance that a positive result is correct and is calculated as follows:
True positives / (True positives + False Positives )

Question 9

What is the negative predictive value and how is it calculated?

Answer 9

The negative predictive value is a measure of the chance that a negative result is correct and is calculated as follows:
True negatives / (True negatives + False negatives )

Question 10

What is the mode?

Answer 10

The most frequent observation

Question 11

What is the robustness of a test?

Answer 11

Reliability of the test, in terms of how well it maintains precision, when certain variables (including test conditions) are changed. Examples of such variables are sample type and sample quality, as well as technicians/analysts, instruments, reagent lots etc.

Question 12

What is the limit of detection?

Answer 12

For quantitative tests, where the result can have any value between two limits, this is the lowest quantity of analyte that can be reliably detected by the test.

Question 13

What is the limit of quantification?

Answer 13

The extremity at which accurate quantification can still be achieved.

Question 14

What are type I and type II error?

Answer 14

Type I: Rejecting the null hypothesis when it’s true.

Type II: Not rejecting the null hypothesis when it’s false

Question 15

What is a p value?

Answer 15

The probability of finding the observed, or more extreme, results when the null hypothesis (H0) of a study is true

Question 16

When should you use non-parametric testing?

Answer 16

• No assumption that the underlying distribution comes from a specific family.
• Very small sample size
• Lots of outliers
• Data is better represented by the median.