Science Of Practice

Question 0

Incidence

Answer 0

The number of new cases arising in a given period of time in a specified population.

Question 1

Prevalence

Answer 1

The number of cases within a defined population at a specific time

Question 2

Risk

Answer 2

Number of cases divided by total population being studied

Question 3

Relative risk

Answer 3

Risk in intervention group divided by risk in placebo group. Used to measure effect in a cohort study.

Question 4

Confounding factor

Answer 4

Background variable which is different between the groups being compared and affects the outcome being studied.

Question 5

Experimental studies

Answer 5

Individuals randomised to control and intervention groups by investigator. E.g. Double blind, single blind, and unblinded.

Question 6

Crossover study

Answer 6

‘Within patient’ study. Each patient receives treatment then placebo in random order. For chronic incurable disorders.

Question 7

Observational study

Answer 7

Predefined groups, results merely observed over time.

Question 8

Case-control study

Answer 8

Retrospective comparison between groups (looking at the past)

Question 9

Cross-sectional study

Answer 9

Comparison at the present time

Question 10

Cohort study

Answer 10

Comparison of future differences (looking at the future)

Question 11

Odds ratio

Answer 11

Number of cases divided by the number of non-cases. Appropriate for case-control studies.

Question 12

Mode

Answer 12

Value which occurs most often

Question 13

Median

Answer 13

Middle value in a ranking (50th centile)

Question 14

Mean

Answer 14

Arithmetic average

Question 15

Left skew

Answer 15

Tail points to the left, most data is at the ‘higher’ end. Mean < median < mode.

Question 16

Right skew

Answer 16

Tail points to the right. Most data is lower. Mode < median < mean

Question 17

Standard deviation

Answer 17

Measure of variance. Approx 68% of values within one SD, 95% within 2 SD.

Question 18

Standard error

Answer 18

Standard deviation divided by the square root of the sample size. Used as a measure of how precisely the sample mean approximates to the population mean. Small for large samples. Used to construct confidence intervals.

Question 19

P value

Answer 19

The probability of observing a difference of that magnitude of the null hypothesis is true.

Question 20

Null hypothesis

Answer 20

The hypothesis that there is not difference between the two groups.

Question 21

Type 1 error

Answer 21

Disbelieving the null hypothesis when it is actually true (because the p-value is low).

Question 22

Type 2 error

Answer 22

Accepting the null hypothesis because the p-value is high while the null hypothesis is actually false. Small samples often lead to type 2 errors because there is insufficient power to detect differences of clinical importance.

Question 23

Power of a study

Answer 23

The probability (as a percentage) of correctly rejecting the null hypothesis when it is false.

Question 24

Parametric tests

Answer 24

Assume that the data is normally distributed (e.g. t-tests, Pearson’s coefficient of linear correlation).

Question 25

Unpaired t-test

Answer 25

A two sample t-test used to compare the average values of two independent groups (e.g treatment vs placebo).

Question 26

Non-parametric tests

Answer 26

For skewed data (e.g. Wilcoxon, Sign, Spearman’s Rank Correlation, Mann-Whitney U, Chi-squared)

Question 27

Correlation coefficient (r)

Answer 27

Indicates how closely points lie to a line. -1-> +1. The closer it is to 0, the less the linear association between the 2 variables.

Question 28

Regression equation

Answer 28

y = a + bx may be used to predict one variable from another. a is the intercept. b is the slope - the regression coefficient

Question 29

Sensitivity

Answer 29

The proportion of true positives correctly identified by the test.

Question 30

Specificity

Answer 30

The proportion of true negatives correctly identified by a test.

Question 31

Positive predictive value

Answer 31

Proportion of those who test positive who actually have the disease.

Question 32

Negative predictive value

Answer 32

The proportion who test negative who do not have the disease.

Question 33

Likelihood ratio for a positive test

Answer 33

Sensitivity / (1 - specificity)

Can be multiples by pre-test odds to give post-test odds.

Question 34

Likelihood ratio for a negative test

Answer 34

(1 - sensitivity) / specificity

Can be multiples by pre-test odds to give post-test odds.