2- Sampling Variation, Bias and Confounding Flashcards

1
Q

When sampling a population what do we need it to be?

A
  • Unbias
  • Representative
  • Precise
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2
Q

What are the two types of error that may occur in a study?

A

- Random (chance): decreases as sample size increases

- Bias (systematic): does not decrease. quantified by difference between true value and actually value

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3
Q

How do you increase precision?

A

Increase sample size. Decreases uncertainty

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4
Q

What are sources of bias?

A

- Selection Bias

- Information Bias

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5
Q

What are some selection biases?

A

1. Non-representative study sample

2. Groups within study may not be comparable

3. Healthy worker effect (people who aren’t working may be due to illness and disease so not necessarily the fact they aren’t working that is causing them to die)

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6
Q

What are some information biases?

A

- Recall error

- Interviewer/Observer error (predispositions)

- Measurement error (measurer or equipment)

  • Misclassification (some people without disease diagnosed as having disease, mainly due to measurement or observational error)
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7
Q

What does no bias, high precision look like?

A
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8
Q

Does a large study mean less bias?

A

NO!

but means more precise

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9
Q

Define prevalence.

A

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

NOT A RATE - per 1000 people then made into a percetage

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10
Q

Define incidence and state how you can calculate incidence rate?

A

Incidence is the number of new cases of a diseases within a given time frame.

Useful when monitoring epidemics

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11
Q

What is person years and how is it calculated?

A

Sum of the total time of everybody followed up in a study

e. g 3 people followed for 5 years and two people followed for 3 years =
(3x5) + (2x3) = 21 py’s

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12
Q

How else can prevalence be measured?

A

Incidence x Duration of Disease

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13
Q

What is the IRR and how is it calculated?

A

Incidence Rate Ratio

Used to compare rate of incidence in two groups

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14
Q

What is relative risk? (a.k.a risk ratio)

A

Absolute risk of one group / Absolute risk of another group

The comparison of the probability of an event occuring in one group compared to another

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15
Q

What factors affect the length of a disease?

A
  • Mortality
  • Curability
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16
Q

How do you work out the odds of an event occuring?

A

It is a ratio

Diseased/Non-diseased for example

or

P/1-P

17
Q

What is the odds ratio?

A

Odds ratio is ratio of odds of outcome in groups defined by levels of exposure at a particular time

Comparison of odds of disease in two groups

18
Q

When can relative risk and odds ratios be used?

A
  • When all patients in the groups have been consistently followed up
19
Q

What is the absolute risk of disease?

A

Disease/Diseased+Non-diseased

20
Q

How do we interpret OR?

A

- Ratio < 1: risk of the group of interest is less than the risk of the comparison group

- Ratio of 1: risk of the group of interest is the same as the risk of the comparison group

- Ratio > 1: risk of the group of interest is greater than the risk of the comparison group

21
Q

What is risk difference?

A

Absolution difference in risk between two groups. If zero there is no difference in risk

22
Q

What is a confounding variable?

A

An unobserved factor that impacts both exposure and can cause disease

or

When comparing groups the association between exposure and outcome is distorted by another variable

e.g alcohol, gender, mouth cancer

23
Q

How can we account for confounding variables?

A

- Standardisation: e.g weight, age, sex

  • Some confounding variables unknown so difficult to address