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STAT PSY3062 > Moderation and simple slopes > Flashcards

Moderation and simple slopes Flashcards

1
Q

Define

Moderation

A

conditions where the effect or relationship of a predictor with the outcome depends upon another variables

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2
Q

Define

Simple slope analysis

A

the regression of the outcome y on the predictor x at a specific value of the moderator m

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3
Q

Define

Enhancing moderator

A

Moderators that strengthen the association

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4
Q

Define

Buffering moderator

A

Moderators that reduce the association

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5
Q

Define

Antagonistic moderator

A

Moderators that flip the direction of the association

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6
Q

Define

Centering

A

The process where we take a variable and change its location so that it has a new center

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7
Q

Definition

conditions where the effect or relationship of a predictor with the outcome depends upon another variables

A

Moderation

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8
Q

Definition

the regression of the outcome y on the predictor x at a specific value of the moderator m

A

Simple slope analysis

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9
Q

Definition

Moderators that strengthen the association

A

Enhancing moderator

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10
Q

Definition

Moderators that reduce the association

A

Buffering moderator

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11
Q

Definition

Moderators that flip the direction of the association

A

Antagonistic moderator

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12
Q

Definition

The process where we take a variable and change its location so that it has a new center

A

Centering

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13
Q

What is the difference between a main effect and an interaction?

A

A main effect is the effect of one factor (IV) on its own.

An interaction examines two or more factors at the same time – that is, their combined effect, which may not be predictable based on the effects of either factor on their own.

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14
Q

What type of moderator is sex in this example?

A
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15
Q

What is the difference between moderation and interaction?

A

Moderation and interaction are used interchangeably. Generally, we use interaction for factors in ANOVAs and moderation to describe a second IV in a regression that moderates another IV

In both cases, an interaction between two variables means that the association between one IV and the DV depends on (i.e., is moderated by) the other IV.

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16
Q

What are the three types of moderators?

A

Enhancing

Buffering

Antagonistic

17
Q

What is moderation?

A

Moderation refers to conditions where the effect or relationship of a predictor with the outcome depends upon another variable

Moderation implies that the relationship between two variables is not the same for everyone

18
Q

In this example what is the moderator?

Stress predicts more negative affect, but responses to stress depend on coping strategies

A

Coping strategies

19
Q

How is moderation statistically measured?

A

Through interactions between two or more variables

20
Q

What types of variables can interactions be measured for?

A

In regression, interactions can be between two categorical variables, two continuous variables, or a categorical and a continuous variable

Interactions between more than two variables work similarly, but interpretation becomes more challenging

In regression, interactions are added as additional variables

21
Q

If the regression equation is: SWLS = b0+ (b1 * Age )+ (b2 * Stress), what would the equation be if an interaction between age and stress was added?

A

SWLS = b0+ (b1 * Age) + (b2 * Stress) + (b3 * Age_x_Stress)

22
Q

Rearrange this equation to pull out age

SWLS = b0+ (b1 * Age) + (b2 * Stress) + (b3 * Age_x_Stress)

A

SWLS = b0+ b1 * Age + b2 * Stress + b3 * (Age * Stress)

SWLS = b0+ b1 * Age + b3 * (Age * Stress) + b2 * Stress

SWLS = b0+ (b1+ b3 * Stress) * Age + b2 * Stress

23
Q

For the following equation, what happens when stress = 0, 5 and 10?

SWLS = 4 + 1.2 * Age + 2 * Stress + 0.5 * (Age * Stress)

A

The slope and intercept increases as stress increases

When Stress = 0:

SWLS = 4 + (1.2 + 0.5 * 0) * Age + 2 * 0

SWLS = 4 + 1.2 * Age + 0

SWLS = 4 + 1.2 * Age

When Stress = 5:

SWLS = 4 + (1.2 + 0.5 * 5) * Age + 2 * 5

SWLS = 4 + 3.7 * Age + 10

SWLS = 14 + 3.7 * Age

When Stress = 10

SWLS = 4 + (1.2 + 0.5 * 10) * Age + 2 * 10

SWLS= 4 + 6.2 * Age + 20

SWLS = 24 + 6.2 * Age

24
Q

What does b3 represent in this equation?

SWLS = b0+ b1 * Age + b2 * Stress + b3 * (Age * Stress)

A

b3 = estimated difference in b1 slope when Stress changes 1-unit OR difference in b2 slope when Age changes 1-unit

25
Q

How do we typically calculate high and low values for a moderator?

A

A common way to define ‘high’ and ‘low’ for the moderator to calculate simple slopes is Mean +/- 1 SD

Suppose Mean Age = 55, SD = 9

Low Age = 55 – 9 = 46

High Age = 55 + 9 = 64

26
Q

What is b4 and b5 in this equation?

SWLS = b0+ b1 * D_SomeUni + b2 * D_Grad + b3 * Stress + b4 * D_SomeUni x Stress + b5 * D_Grad x Stress

A

b4 = estimated difference in slope / mean difference for ‘SomeUni’ Education or for a one unit change in Stress

b5 = estimated difference in slope / mean difference for ‘Grad’ Education for a one unit change in Stress

27
Q

Why would we want to seen if a continuous variable interacts with itself?

A

To see if the relationship is truly linear.

If the relationship is linear, there will be no difference in slopes

28
Q

Why do we center values in calculating interactions?

A

When interactions are in a model, the default simple slopes estimated are for when the variables involved in the interaction are equal to zero

If the range of outcomes does not include zero, the default simple slopes are meaningless and not easy to interpret

Therefore we select a centre value and subtract all of out data by that values

i.e. Stress20 = Stress - 20

29
Q

What are the assumptions of interactions and simple slope calculations?

A

DV (Y) is continuous

One IV (the X) is continuous (if both X and moderator (M) are categorical, you want to do a factorial ANOVA)

Independence of observations

No multicollinearity

No significant outliers

CAUTION: Causality – moderators can suggest possible mechanisms/mediators

Linearity (X and Y)

Homogeneity of variance

STAT PSY3062 (9 decks)

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