Applied statistics and interpreting results

Question 1

Describe the types of data used/found in clinical trials

Answer 1

Binary = two possible responses (Yes/No)

Continuous = e.g. blood pressure, cholesterol

Time-to-event = time to particular outcome (death, pregnancy)

Question 2

Describe what categorical data is

Answer 2

Consists of nominal (categories not ordered –> ethnic groups) and ordinal (Categories are ordered –> tumour stages)

Question 3

Describe what nominal data is

Answer 3

Gives averages and means; consists of:

Discrete = only finite values possible (e.g. hospital admission)

Continuous = all values are theoretically possible (e.g. height)

Question 4

Compare parametric testing and non-parametric testing

Answer 4

Parametric = assumes normal distribution, gives significant result more often

Non-parametric tests = comparison of rank order, not influenced by outliers much

Question 5

What is a null hypothesis?

Answer 5

Population for which the sample was obtained, no difference exists in response to treatment A vs B

Nothing happens when experiment is completed

Question 6

What is the alternate hypothesis?

Answer 6

Hypothesises that a difference exists in the response to treatment A compared to B

Question 7

Describe a type I error (alpha)

Answer 7

Probability of falsely rejecting Ho (null) and detecting a stat sig difference when no difference exists in reality

False positive

Question 8

Describe a type II error (beta)

Answer 8

Probability of falsely accepting the H0 (null) and not detecting stat sig diff when specified difference between grps exists

False negative

Question 9

Describe what power (1-beta) is

Answer 9

Probability of correctly rejecting null (H0) and detecting a stat sig diff when specified difference between the groups in reality exists

The higher the power, the better

Question 10

What do you use to measure the effect of binary data?

Answer 10

Risk difference (Absolute risk difference)

Relative Risk (RR)

Odds Ratio (OD)

Number Needed to Treat

Number Needed to Harm

Question 11

Explain absolute risk (risk difference, risk inc, risk dec)

Answer 11

Absolute risk difference = diff between absolute risk of event in intervention and absolute risk of event in control group

Absolute risk reduction = treatment is effective and reduces risk of unwanted event

Absolute risk inc = treatment does not work, inc risk of event

Question 12

What is the number needed to treat (NNT)?

Answer 12

Number of patients who needed to be treated to produce one additional successful outcome

Useful in comparing efficacy of treatments

Question 13

What is the number needed to harm (NNH)?

Answer 13

Number of patients who need to be treated to produce one additional adverse event

Question 14

Describe what relative risk is

Answer 14

Also known as risk ration, risk of an event (outcome) occurring

Where 1.0 is the middle number

If risk is death, you want the number to be low

If risk is cure, you want the number to be higher

Question 15

What is the odds ration?

Answer 15

Probability of an event occurring over the risk of an event not occurring

Question 16

What is selection bias?

Answer 16

Choosing participants in a way to underrepresent or overrepresent in a study

Does not represent the true population

Question 17

What is performance bias?

Answer 17

Unequal care between experimental groups

Question 18

What is attrition bias?

Answer 18

When participants who drop out of the study systematically differ from those who remain

Question 19

What is detection bias?

Answer 19

Systematic difference between groups in how outcomes are determined

e.g. When the outcome of event is discovered using a different measure/method/criteria

Question 20

What is the P value?

Answer 20

States the probability that the finding is due to chance or an actual difference.

Determines statistical significance

<0.05 = stat sig

> 0.05 = not stat sig

Question 21

What is the confidence interval?

Answer 21

Gives estimate of precision of result; represents the range of values within which we are 95% confident that true population estimate lies

Says that, if trial was to be repeated, the findings will fall in that data range 95% of the time

Question 22

What is a significant result in the context of CI?

Answer 22

CI is stat sig if it does not cross the null

1.0 for Relative Risk

0 for absolute risk reduction

Question 23

What is the difference between statistical significance and clinical significance?

Answer 23

Stat sig = relates to size of effect and the 95% CI in relation to null hypothesis

Clinical sig = relates to size of the effect and the CI in relation to a minimum effect that would be considered clinically important

Question 24

Describe what intention to treat is in RCT

Answer 24

It is a method for analysing results in a prospective randomised study where all participants who are randomised are included in the stat analysis

They are analysed according to the group that they were assigned