Clinical Sciences: Statistics, studies and other shizz

Question 1

Mean

Answer 1

The average of a series of observed values

Question 2

Median

Answer 2

The middle value if series of observed values are placed in order

Question 3

Mode

Answer 3

The value that occurs most frequently within a dataset

Question 4

Range

Answer 4

The difference between the largest and smallest observed value

Question 5

Randomised controlled trial

Answer 5

Participants randomly allocated to intervention or control group (e.g. standard treatment or placebo)

Question 6

Cohort study

Answer 6

Observational and prospective. Two (or more) are selected according to their exposure to a particular agent (e.g. medicine, toxin) and followed up to see how many develop a disease or other outcome.

Question 7

Cohort study outcome measure

Answer 7

RELATIVE RISK

Question 8

Case-control study

Answer 8

Observational and retrospective. Patients with a particular condition (cases) are identified and matched with controls. Data is then collected on past exposure to a possible causal agent for the condition.

Question 9

Case-control study outcome measure

Answer 9

The usual outcome measure is the odds ratio.

Question 10

Cross-sectional survey

Answer 10

Provide a ‘snapshot’, sometimes called prevalence studies

Question 11

Specificity formula

Answer 11

TN / (TN + FP)

Question 11

Sensitivity formula

Answer 11

TP / (TP + FN )

Question 12

Positive predictive value formula

Answer 12

TP / (TP + FP)

Question 13

Negative predictive value formula

Answer 13

TN / (TN + FN)

Question 14

Likelihood ratio for a positive test result

Answer 14

sensitivity / (1 - specificity)

Question 15

Likelihood ratio for a negative test result

Answer 15

(1 - sensitivity) / specificity

Question 16

Sensitivity definition

Answer 16

Proportion of patients with the condition that have a positive test result

Question 17

Specificity definition

Answer 17

Proportion of patients without the condition who have a negative test result

Question 18

Positive predictive value

Answer 18

The chance that the patient has the condition if the diagnostic test is positive

Question 19

Negative predictive value

Answer 19

The chance that the patient does not have the condition if the diagnostic test is negative

Question 20

Likelihood ratio for a positive test result

Answer 20

How much the odds of the disease increase when a test is positive

Question 21

Likelihood ratio for a negative test result

Answer 21

How much the odds of the disease decrease when a test is negative

Question 22

Confidence interval

Answer 22

a range of values within which the true effect of intervention is likely to lie

Question 23

Standard error of the mean

Answer 23

The standard error of the mean (SEM) is a measure of the spread expected for the mean of the observations - i.e. how ‘accurate’ the calculated sample mean is from the true population mean

Question 24

How to calculate SEM

Answer 24

SD / square root (n)

Question 25

Standard deviation

Answer 25

measure of how much dispersion exists from the mean

Question 26

Clinical trial Phase 1

Answer 26

Determines pharmacokinetics and pharmacodynamics and side-effects prior to larger studies

Question 27

Clinical trial phase 2

Answer 27

Assess efficacy + dosage

Question 28

Clinical trial phase 3

Answer 28

Assess effectiveness

Question 29

Clinical trial phase 4

Answer 29

Postmarketing surveillance

Question 30

What does parametric mean?

Answer 30

something which can be measured, usually normally distributed

Question 31

Name 2 parametric tests

Answer 31

Student’s t-test - paired or unpaired*
Pearson’s product-moment coefficient - correlation

Question 32

Name 4 Non-parametric tests

Answer 32

Mann-Witney U test
Wilcoxon signed rank test
Chi-squared test
Spearman rank, Kendall Rank

Question 33

Mann-Whitney U test - what does it do?

Answer 33

compares ordinal, interval, or ratio scales of unpaired data

Question 34

Wilcoxon signed-rank test - what does it do?

Answer 34

compares two sets of observations on a single sample, e.g. a ‘before’ and ‘after’ test on the same population following an intervention

Question 35

chi-squared test - what does it do?

Answer 35

used to compare proportions or percentages e.g. compares the percentage of patients who improved following two different interventions

Question 36

Spearman / Kendall test- what does it do?

Answer 36

Correlation

Question 37

p value

Answer 37

the probability of obtaining a result by chance at least as extreme as the one that was actually observed, assuming that the null hypothesis is true

Question 38

type I error

Answer 38

the null hypothesis is rejected when it is true (false positive)

Question 39

type II error

Answer 39

he null hypothesis is accepted when it is false (false negative)

Question 40

The power of a study

Answer 40

The power of a study is the probability of (correctly) rejecting the null hypothesis when it is false, i.e. the probability of detecting a statistically significant difference

Question 41

nominal data

Answer 41

Observed values can be put into set categories which have no particular order or hierarchy. You can count but not order or measure nominal data (for example birthplace)

Question 42

Ordinal data

Answer 42

Observed values can be put into set categories which themselves can be ordered (for example NYHA classification of heart failure symptoms)

Question 43

Discrete data

Answer 43

Observed values are confined to a certain values, usually a finite number of whole numbers (for example the number of asthma exacerbations in a year)

Question 44

Continuous data

Answer 44

Data can take any value with certain range (for example weight)

Question 45

Binomial data

Answer 45

Data may take one of two values (for example gender)

Question 46

Interval data

Answer 46

A measurement where the difference between two values is meaningful, such that equal differences between values correspond to real differences between the quantities that the scale measures (for example temperature)