Session 2 Lecture 1: Measurement-Scales, Numbers, Rates, Ratios and Risk

Question 1

What are the 3 key features of the sample population taken to make an inference about the entire population?

Answer 1

• Representative
• Unbiased
• Precise

Question 2

State the two type of error that can occur in a study that may influence the results

Answer 2

• Chance (Random error)

- Bias (Systematic error)

Question 3

How does Chance (Random error) occur?

Answer 3

• Due to sampling variation

- will reduce as sampling size increases

Question 4

How does Bias (Systematic error) occur?

Answer 4

• Quantified by the difference between the true value and the expected value
• Does not reduce as sample size increases, bias remains the same

Question 5

Where does the bias come from that leads to Systematic error?

Answer 5

• Selection biases

- Information biases in the data

Question 6

Examples of selection biases which are a source of bias that can lead to Systematic error

Answer 6

-Study Sample (External Validity)
not representative of pop of interest

-Group selection within a study (Internal Validity)
groups within a study may not be comparable

-Healthy worker effect
workers usually exhibit lower overall mortality than the general pop

Question 7

Examples of Information biases in the data which are a source of bias that can lead to Systematic error

Answer 7

-Recall error
differences in recollection from study participants regarding events or experiences from the past

-Observer/interviewer error
study observer/interviewer may have preconceived expectations or knowledge that may influence the result

-Measurement error
Differences in the measurements of participants

-Misclassification
participants put in wrong group

Question 8

Define the term Prevalence

Answer 8

The proportion of people who have a disease at a given point in time

Question 9

Calculating prevalence

Answer 9

Number of people with disease / total population (number of people)

Question 10

Define the term Incidence

Answer 10

The number of new cases of a disease within a given timeframe

Question 11

Calculating Incidence rate

Answer 11

Number of new cases / sum of the patient time at risk

• patient time at risk = Sum of all the patients times at risk

often reported as a rate: events per person per year (50 per 100000 person-years)

Question 12

What is the Incidence Rate Ratio used for?

Answer 12

• To compare the incidence rate in one group to another
• relative measure between 2 groups

IRR = incidence rate in group A / incidence rate in group B

Group A= group you are interested in
Group B=comparing group

Question 13

Calculating Odds

Answer 13

If the probability of an event is p then the odds of that event is given by:

Odds=p/1-p

Question 14

What is the ratio of odds used for?

Answer 14

To compare two exposure groups

Question 15

What is the Odds Ratio?

Answer 15

A relative comparison of the odds of an event happening in Group A compared to Group B

“The ratio of ratios”

Question 16

How is the Odds ratio calculated?

Answer 16

odds of group A = a/b
——————————– = ad/bc
odds of group B= c/d

Question 17

How is the absolute risk calculated?

Answer 17

Group A = a / a+b

Group B = c / c+d

Question 18

Calculating relative risk

Answer 18

Absolute risk for group A/Absolute risk for group B

Question 19

What is the null value for the Odds ratio and relative risk?

Answer 19

1

Question 20

What is the interpretation if the Odds ratio (OR) and relative risk (RR) are < 1 respectively?

Answer 20

OR < 1 = numerator has a lower odds of the event

RR < 1 = numerator has a lower risk of the event

Question 21

What is the outcome of the event when the desirable interpretation of odds ratio and relative risk is < 1?

Answer 21

Desired if the event is a bad outcome

Question 22

What is the interpretation if the Odds ratio (OR) and relative risk (RR) are > 1 respectively?

Answer 22

OR > 1 = numerator has a greater odds of the event

RR > 1 = numerator has a greater risk of the event

Question 23

What is the outcome of the event when the desirable interpretation of odds ratio and relative risk is >1?

Answer 23

Desired if the event is a good outcome

Question 24

Calculating the Risk difference

Answer 24

Absolute risk in Group A - Absolute risk in Group B

=Absolute difference

Question 25

What is the null value for Risk difference?

Answer 25

0

Question 26

What are the issues to be aware of when comparing groups?

Answer 26

Confounding issues

Question 27

What do Confounding issues affect?

Answer 27

They affect both exposure and outcome.

When comparing groups, the association or effect between an exposure and outcome is distorted by the presence of another variable

Question 28

What can be done about confounding factors?

Answer 28

In stats, we can adjust for differences in known confounding factors

-Standardisation

however, a lot of confounding factors are unknown