RESS

Question 1

What must a sample be when trying to make assumptions about a population?

Answer 1

Representative of that population

Question 2

Name the 2 types of categorical data, and describe each.

Answer 2

Nominal: no natural ordering e.g. sex, eye colour
Ordinal: have categories that are ordered, e.g. stage in disease: absent, mild, severe

Question 3

Name the two types of numerical data, and describe each.

Answer 3

Discrete: only whole number values, e.g. number of hospital visits.
Continuous: values with no limitations, e.g. weight

Question 4

Which average and spread should be used for normally distributed data?

Answer 4

Mean and standard deviation

Question 5

Which average and spread should be used for skewed data?

Answer 5

Median and inter-quartile range

Question 6

What is incidence?

Answer 6

Number of new cases of a disease, measured over specified period.
Number of new cases/number at risk.

Question 7

How do you use incidence to calculate the number at risk?

Answer 7

Number at risk halfway through the specified period

Question 8

What leads to inaccuracies in using incidence to calculate risk, and how would you overcome this

Answer 8

If the number at risk varies over time. Calculate person-time risk instead, which is to add up the length of time that all people are at risk.

Question 9

What is prevalence?

Answer 9

Number of people with disease at a specific time.

Number of people with disease / total population

Question 10

What is the case fatality rate?

Answer 10

Number of people who die from a disease / number of people with the disease. Measured over specified time period.

Question 11

Mortality rate

Answer 11

Number of people who die from disease / number of people in the population, over specified period

Question 12

Risk

Answer 12

Number of new cases / number at risk. E.g. number of hospital-acquired infections in cancer inpatients / total number of cancer inpatients

Question 13

Risk ratio

Answer 13

Comparison of risk between two groups - exposure and control.
Risk in exposed group / risk in unexposed group. Also called relative risk

Question 14

When are odds used?

Answer 14

Where risk cannot be calculated, e.g. in case control studies

Question 15

Odds calculation

Answer 15

Probability of an event / probability event does not occur

Question 16

Odds ratio

Answer 16

Comparison of odds between two groups. Odds in exposed group / odds in unexposed group

Question 17

What does a RR or OR of 1 mean

Answer 17

No difference in effect between the two groups

Question 18

What does a RR or OR of less than 1 mean

Answer 18

The risk/odds in the exposed group is less than in the control group i.e. the exposure is protective

Question 19

What does a RR or OR of more than 1 mean

Answer 19

Risk/odds in the exposed group is more than that in the control group i.e. the exposure is harmful

Question 20

In a normal distribution, 95% data lie within ________ standard deviations

Answer 20

1.96

Question 21

Standard error calculation

Answer 21

Standard deviation / square root of sample size

Question 22

95% confidence interval calculation

Answer 22

mean ± (1.96 x standard error)

Question 23

Null hypothesis

Answer 23

There will be no relationship between exposure and outcome

Question 24

What is “no effect”

Answer 24

Differs for different comparisons. Difference: no effect = 0

Ratio: no effect = 1

Question 25

How do you use confidence intervals to reject the null hypothesis?

Answer 25

If the confidence interval does not cross "no effect", then the effect is statistically significant, and the null hypothesis is rejected.

Question 26

What is meant by p<0.05

Answer 26

The effect is statistically significant.

Question 27

Correlation

Answer 27

Linear association between two continuous variables - one exposure, one outcome.

Question 28

Graph to show correlation

Answer 28

Scatterplot

Question 29

Linear regression

Answer 29

Extends correlation to consider other confounding variables. Allows you to give and equation for line of best fit to make predictions.

Question 30

Chi-squared is used to

Answer 30

Determine the association between categorical variables

Question 31

Primary prevention

Answer 31

Remove the cause

Question 32

Secondary prevention

Answer 32

Screen for the disease

Question 33

Tertiary prevention

Answer 33

Prevent the disease by treating clinical cases

Question 34

Sensitivity

Answer 34

True positive. How well does the test detect the condition? = number who correctly test positive / total number with disease

Question 35

Specificity

Answer 35

True negative How good is the test at correctly excluding people without the disease. = number who correctly test negative / total number of people without the disease

Question 36

Positive predictive value

Answer 36

If a person tests positive, what is the probability they have the condition? Number who correctly test positive / total number who test positive

Question 37

Negative predictive value

Answer 37

If a person tests negative, what is the probability that they do not have the condition? Number who correctly test negative / total number who test negative

Question 38

Test accuracy

Answer 38

Proportion of all tests that have given the correct result. | (Number who correctly test positive + number who correctly test negative)/total number of tests