Lesson test: Confounding and randomisation

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Confounding and randomisation

1.[3p]
What makes a variable a confounder?

It affects the outcome, is associated with the exposure, and is not on the causal path between them

Correct

It is correlated with the outcome

The answer is: It affects the outcome, is associated with the exposure, and is not on the causal path between them

It was not measured in the study

The answer is: It affects the outcome, is associated with the exposure, and is not on the causal path between them

It lies on the causal path from exposure to outcome

The answer is: It affects the outcome, is associated with the exposure, and is not on the causal path between them

2.[2p]
Berkeley's six largest departments admitted 44.5 per cent of men and how many per cent of women, to one decimal place?

CorrectNot quite: 30.3

3.[3p]
What produced the Berkeley reversal?

Women applied disproportionately to departments with low admission rates

Correct

Women were rejected more often within each department

The answer is: Women applied disproportionately to departments with low admission rates

The sample of women was too small to analyse

The answer is: Women applied disproportionately to departments with low admission rates

Admission rates were recorded incorrectly

The answer is: Women applied disproportionately to departments with low admission rates

4.[3p]
Randomisation guarantees that the treatment and control groups are balanced on every covariate in any particular trial.

True

The answer is: False

False

Correct

5.[2p]
A trial randomises 50 per arm and ages have standard deviation 12 years. What is the standard error of the difference in mean age, in years?

CorrectNot quite: 2.4

6.[3p]
If 20 baseline covariates are each tested at the 5 per cent level, what is the probability that at least one comes out significant, to two decimal places?

CorrectNot quite: 0.64

7.[3p]
Why did observational studies of hormone replacement therapy disagree with the randomised trial?

Select all that apply

Women who chose HRT differed from those who did not in ways nobody had measured

Correct

Adjustment can only remove confounders that were measured and correctly identified

Correct

A clean residual plot does not rule out a large omitted variable

Correct

The observational studies used the wrong significance threshold

The answer is: Women who chose HRT differed from those who did not in ways nobody had measured, Adjustment can only remove confounders that were measured and correctly identified, A clean residual plot does not rule out a large omitted variable

8.[3p]
Match each design device to what it achieves.

Randomisation
Blinding
Blocking
Stratified randomisation

removes block-to-block variation
hides the assignment from both sides
removes confounding, measured or not
forces balance on one variable

Show the answer

Randomisation: removes confounding, measured or not Blinding: hides the assignment from both sides Blocking: removes block-to-block variation Stratified randomisation: forces balance on one variable

9.[2p]
Why is adjusting for a variable on the causal path a mistake?

It removes the mechanism through which the exposure acts, erasing part of the real effect

Correct

It always increases the standard error

The answer is: It removes the mechanism through which the exposure acts, erasing part of the real effect

Variables on the causal path cannot be measured

The answer is: It removes the mechanism through which the exposure acts, erasing part of the real effect

It converts a confounder into a collider

The answer is: It removes the mechanism through which the exposure acts, erasing part of the real effect

1.[3p] What makes a variable a confounder?

2.[2p] Berkeley's six largest departments admitted 44.5 per cent of men and how many per cent of women, to one decimal place?

3.[3p] What produced the Berkeley reversal?

4.[3p] Randomisation guarantees that the treatment and control groups are balanced on every covariate in any particular trial.

5.[2p] A trial randomises 50 per arm and ages have standard deviation 12 years. What is the standard error of the difference in mean age, in years?

6.[3p] If 20 baseline covariates are each tested at the 5 per cent level, what is the probability that at least one comes out significant, to two decimal places?

7.[3p] Why did observational studies of hormone replacement therapy disagree with the randomised trial?

8.[3p] Match each design device to what it achieves.

9.[2p] Why is adjusting for a variable on the causal path a mistake?

1.[3p]
What makes a variable a confounder?

2.[2p]
Berkeley's six largest departments admitted 44.5 per cent of men and how many per cent of women, to one decimal place?

3.[3p]
What produced the Berkeley reversal?

4.[3p]
Randomisation guarantees that the treatment and control groups are balanced on every covariate in any particular trial.

5.[2p]
A trial randomises 50 per arm and ages have standard deviation 12 years. What is the standard error of the difference in mean age, in years?

6.[3p]
If 20 baseline covariates are each tested at the 5 per cent level, what is the probability that at least one comes out significant, to two decimal places?

7.[3p]
Why did observational studies of hormone replacement therapy disagree with the randomised trial?

8.[3p]
Match each design device to what it achieves.

9.[2p]
Why is adjusting for a variable on the causal path a mistake?