Topic 4: Multilevel Model Flashcards

1
Q

What is a multi-level trial

A

When observations are grouped into clusters

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2
Q

What is a multi-centre trial

A

Carried out at more than one medical insitution

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3
Q

What are the 3 types of multilevel design

A

Nested, crossed, repeated measure

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4
Q

What gets randomised in a nested design

A

The clusters are randomised. Therefore the clustering is imposed by the design

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5
Q

Why are multilevel trials different to other trials

A

Assumption of independence is violated, there is dependence among observations from that cluster. A larger sample size is needed for cluster randomisation, analysis must take clustering into account.

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6
Q

What is a crossed design termed

A

Background clustering

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7
Q

What is randomised in a nested design

A

Individuals, patients within clusters as opposed to the clusters themselves

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8
Q

What is a repeated measures design

A

Several measurements taken from the individual over a period of time

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9
Q

True/False: A nested and crossed design can have repeated measures

A

True

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10
Q

What is between cluster variation

A

Variation in the true means in outcome between clusters

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11
Q

What is within cluster correlation

A

Correlation between pairs of individuals in the same cluster - same for all pairs of individuals in the cluster

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12
Q

What is within cluster variance

A

How far each point is to the cluster specific mean. The variance within each cluster.

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13
Q

How is within cluster correlation measured

A

Intra-class correlation coefficient - rho

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14
Q

What is the intra-class correlation coefficient

A

The proportion of total variation in your outcome that is accounted for by clustering

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15
Q

What does an intra-class correlation coefficient of 1 mean

A

All individuals from the same cluster have the same outcome. Perfect correlation between individuals in the same cluster

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16
Q

What does an intra-class correlation coefficient of 0 mean

A

No clustering. Individuals within the same cluster are no more similar than individuals from a different cluster.

17
Q

True/False: The ICC is calculated the same way for quantitative and binary outcomes

A

False

18
Q

What does a higher ICC mean/motivate in terms of design

A

Means less unique information given by individuals within the same cluster - motivates more clusters with fewer participants.