Effect Modification (Interaction) Flashcards

1
Q

What is a modifier (Z)?

A

A variable that alters the relationship between the X1 and Y

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

What is the interaction term?

A

The cross-product between X1 and the modifier

X1 x Z

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

If β3 has a p<0.05, what can you conclude about the modification?

A

There is a significant effect modification.

There is a significant interaction between X1 and the modifier Z

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

What are the main effects of the interaction interpretation?

A

β1 and β2

(effect of X1 on Y when Z=0, and effect of Z on Y when X1=0)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

If there is an interaction, how do you calculate the effect of X1 on Y?

A

β1 + β3 x Z

(Z = 0 or 1 if coded, use average if continuous)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

How do you interpret a negative interaction effect?

A

Effect of one variable decreases as the other variable increases

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

How can you present continuous x continuous interactions?

A

▪️Table with quartiles
▪️Graph plotting quartiles

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

What is an outlier?

A

An observation that lies an abnormal distance from other values in a random sample

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

What are influential observations?

A

Outliers with large influence on the fitted regression model

May distort the actual relationship

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

How can you spot outliers in your dataset?

A

▪️Sort by ascending/descending
▪️Look at minimums and maximums
▪️Plot on graph e.g. regression variable plots

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

What are mild outliers?

A

Outliers that lie between 1.5 and 3 times the IQR (below Q1 or above Q3)

(between inner and outer limits)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What are extreme outliers?

A

Outliers that lie more than 3 times the IQR (below Q1 or above Q3)

(beyond outer limit)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

What is the lower outer fence?

A

Q1 - (3 x IQR)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

What is the lower inner fence?

A

Q1 - (1.5 x IQR)

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

How can you find outliers using standardised residuals?

A

Any observation with an absolute standardised residual larger than 3

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

What is DFBETA?

A

For any given observations, measures the change in the estimated coefficient (β) due to deleting the observation (βwith - βwithout)

Standardised DFBETA ÷ SE(est β)

17
Q

What is DFFIT?

A

For any given observation, measures the change in predicted value (Y) due to deleting that observation

DFFIT ÷ SE(Y)

18
Q

What absolute value of DFBETA would suggest an influential observation?

A

> 1

19
Q

What absolute value of standardised DFFIT would suggest an influential observation?

A

> 1

20
Q

Why should you consider outliers?

A

Outliers can:
▪️Increase error variance
▪️Reduce power
▪️Decrease normality
▪️Violate assumptions of sphericity
▪️Alter odds of type I and II errors
▪️Bias/influence estimates

21
Q

What should you do if an outlier is a natural part of the population you are studying?

A

Keep it

22
Q

What should you do if an outlier is a measurement or data entry error?

A

Correct it if possible, if not remove it

23
Q

What should you do if an outlier is not part of the population you are studying?

A

Remove it

24
Q

What should you do when you remove an outlier?

A

▪️Document exclusion and explain reasoning
▪️Attribute a cause for removing it
▪️Potentially perform analysis with and without, then discuss difference