9: Moderation, Regression, Main Effects And Interactions. Flashcards

1
Q

What type of variables can regression use in moderation?

A

Categorical and continuous.

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2
Q

What do X axis values have implications for?

A

Interpretation of regression values: constant and effect terms.

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3
Q

Why are weight values arbitrary?

A

Changed to the cross-product are matched by changes to the SS for X values.

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4
Q

What does coding matter for?

A

Interpret

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5
Q

What is contrast coding?

A

Where the numbers represent meaningful contrasts between groups

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6
Q

What is dummy coding?

A

The focal group is coded 1 and all others group 0.

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7
Q

What is effect coding?

A

One group is always -1, each of the others in turn are 1, and the rest are 0.

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8
Q

What does coding not effect?

A

Means, F , r, and R^2.

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9
Q

Briefly describe a conditional effect.

A

The impact of Factor A depends on the level of Factor B.

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10
Q

What is implied by an interaction:

A

Simple effects are different in different parts of the design.

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11
Q

Name 2 things which indicate main effects.

A

Gaps between lines at the mid-point and the average slope.

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12
Q

Name 2 things which indicate an interaction.

A

Differences in slopes and differences in gaps (accounting for direction).

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13
Q

What is covered in an omnibus test?

A

The whole set of conditions, and the overall null hypothesis.

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14
Q

Describe planned comparisons.

A

Compare 2 individual means at a time.

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15
Q

Describe complex comparisons.

A

Combine sets of means and then compare them.

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16
Q

What is the name for comparisons which turn everything into a t test?

A

Single df comparisons.

17
Q

How is psi computed in planned comparisons?

A

Sum of products of the contrast weights and the means.

18
Q

How is SS computed in planned comparisons?

A

Psi^2 / sum of squared coefficients.

19
Q

What is the bets estimate of error in planned comparisons?

A

The MSerror from the omnibus test.

20
Q

What is calculated to check if comparisons are orthogonal?

A

The cross-product of the weights.

21
Q

When are combinations of regression vectors not orthogonal?

A

When there are more comparisons/ vecors than degrees of freedom for the effect.

22
Q

How is R^2 max derived from orthogonal sets of contrast vectors?

A

Summing all r^2 values for the contrast vectors with the DV.