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RESS > RESS > Flashcards

RESS Flashcards

1
Q

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

A

Representative of that population

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2
Q

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

A

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

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3
Q

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

A

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

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4
Q

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

A

Mean and standard deviation

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5
Q

Which average and spread should be used for skewed data?

A

Median and inter-quartile range

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6
Q

What is incidence?

A

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

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7
Q

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

A

Number at risk halfway through the specified period

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8
Q

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

A

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.

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9
Q

What is prevalence?

A

Number of people with disease at a specific time.

Number of people with disease / total population

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10
Q

What is the case fatality rate?

A

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

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11
Q

Mortality rate

A

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

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12
Q

Risk

A

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

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13
Q

Risk ratio

A

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

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14
Q

When are odds used?

A

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

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15
Q

Odds calculation

A

Probability of an event / probability event does not occur

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16
Q

Odds ratio

A

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

17
Q

What does a RR or OR of 1 mean

A

No difference in effect between the two groups

18
Q

What does a RR or OR of less than 1 mean

A

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

19
Q

What does a RR or OR of more than 1 mean

A

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

20
Q

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

A

1.96

21
Q

Standard error calculation

A

Standard deviation / square root of sample size

22
Q

95% confidence interval calculation

A

mean ± (1.96 x standard error)

23
Q

Null hypothesis

A

There will be no relationship between exposure and outcome

24
Q

What is “no effect”

A

Differs for different comparisons. Difference: no effect = 0

Ratio: no effect = 1

25
Q

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

A

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

26
Q

What is meant by p<0.05

A

The effect is statistically significant.

27
Q

Correlation

A

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

28
Q

Graph to show correlation

A

Scatterplot

29
Q

Linear regression

A

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

30
Q

Chi-squared is used to

A

Determine the association between categorical variables

31
Q

Primary prevention

A

Remove the cause

32
Q

Secondary prevention

A

Screen for the disease

33
Q

Tertiary prevention

A

Prevent the disease by treating clinical cases

34
Q

Sensitivity

A

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

35
Q

Specificity

A

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

36
Q

Positive predictive value

A

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

37
Q

Negative predictive value

A

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

38
Q

Test accuracy

A

Proportion of all tests that have given the correct result.

(Number who correctly test positive + number who correctly test negative)/total number of tests

RESS (1 decks)

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