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PSYC3010 > Module 1 > Flashcards

Module 1 Flashcards

1
Q

Define interactions:

A

Where a particular effect or relationship between variables changes as a function of another variable (e.g. when the effect of an IV on a DV changes as a function of a second IV)

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2
Q

How do interactions add nuance to established effects?

A

They indicate the conditions under which the effect is likely to be stronger, weaker, non-existent, or even reversed (e.g. boundary conditions)

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3
Q

Define factor:

A

Another term for independent variable in the context of ANOVA

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4
Q

Define levels:

A

Another term for the conditions or groups of the factor

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5
Q

When are one-way ANOVA’s used ?

A

When we are interested in the effect of one factor on a dependant variable

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6
Q

When do we use factorial ANOVA’s?

A

When we are interested in the effect of two or more factors on a DV, as it allows us to examine the effects of two or more factors simultaneously.

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7
Q

What does a factorial design have:

A
  • At least two factors
  • Each with at least two levels
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8
Q

What types of effects foes a two-way factorial ANOVA produce?

A
  1. Main effect of factor A
  2. Main effect of factor B
  3. Factor A x Factor B interaction (does the effect of factor a on the dv change at each level of factor b)
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9
Q

Define the grand mean:

A

The mean of all observed scores

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10
Q

Define marginal means:

A

The average of all scores on each level of one factor, collapsing over levels of the other factor(s).

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11
Q

Define cell means:

A

The average of all scores at each level of one factor, at each level of the other factor(s).

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12
Q

When spotting a potential interaction, what would parallel lines suggest?

A

There is no interaction

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13
Q

When spotting a potential interaction, what would non-parallel lines suggest?

A

There may be an interaction

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14
Q

When spotting a potential interaction, what would the lines crossing suggest?

A

A disordinal interaction

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15
Q

When spotting a potential interaction, what would lines that do not cross, but are not parallel suggest?

A

Ordinal interaction

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16
Q

Define variable:

A

Anything that can vary

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17
Q

Define variance

A

A measure of the dispersion or spread of scores around a point of central tendency

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18
Q

Why is the grand mean included in hypotheses?

A

If there are no differences across the group means (if the null hypothesis is true), all of the means will sit on the grand mean.

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19
Q

Define between-groups variance

A

Systematic variation in DV between the different groups/levels/treatments of the IV (treatment variance)

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20
Q

Define within-groups variance

A

Random variation in DV within the groups that can’t be explained by the IV; due to unmeasured influences (error variance)

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21
Q
A
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22
Q
A
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23
Q

What is a factorial between-participants ANOVA?

A

A statistical method used to analyze the effects of two or more independent variables on a dependent variable across different groups.

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24
Q

What are the key components of a factorial design?

A
  • Independent Variables (IVs)
  • Dependent Variable (DV)
  • Levels of each IV
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25
What is the significance of manipulation checks in psychological research?
To ensure that the independent variable manipulation has been perceived or experienced by participants as intended.
26
Fill in the blank: A manipulation check measure is designed to test the effectiveness of the _______.
[independent variable]
27
What does a significant interaction on the distraction manipulation check indicate?
More complex processes at play.
28
What are higher-order factorial designs?
Factorial designs with more than two factors that allow for a more complex analysis of interactions.
29
What does a three-way interaction in a factorial design indicate?
The interaction between two factors changes depending on the level of a third factor.
30
What is the typical analysis method for a manipulation check?
Conduct a regular factorial ANOVA using the manipulation check measure as the DV.
31
What are the ideal results for a manipulation check?
* Significant main effect of the factor being checked * Non-significant main effects of other factors or interactions
32
What is the purpose of conducting follow-up tests in higher-order ANOVA?
To ensure the direction of effect is established as intended.
33
What type of design is described as a 3 x 2 x 2 between-participants factorial design?
A three-way between-participants factorial design.
34
What does a main effect of a factor indicate?
There is an effect of one factor averaging over the levels of the other factors.
35
What should the y-axis represent when plotting cell means on line graphs?
The dependent variable (DV).
36
In a three-way ANOVA, what does the term 'simple interaction' refer to?
The interaction between two factors at each level of the third factor.
37
What is the significance of the marginal means in factorial designs?
They indicate the average effect of one factor while collapsing over the other factors.
38
What is the first step in analyzing a manipulation check measure?
Conduct a factorial ANOVA.
39
What is a three-way ANOVA?
A statistical test used to evaluate the interaction between three independent variables.
40
What are the research questions addressed by a three-way ANOVA?
* Is there a Factor A x Factor B x Factor C interaction? * Does the A x B interaction change at each level of Factor C? * Does the A x C interaction change at each level of Factor B? * Does the B x C interaction change at each level of Factor A?
41
What are the three main effects in a three-way ANOVA?
* Main effect of Factor A * Main effect of Factor B * Main effect of Factor C
42
What are the two-way interaction effects in a three-way ANOVA?
* A x B Interaction * A x C Interaction * B x C Interaction
43
What is a three-way interaction in a three-way ANOVA?
A x B x C Interaction
44
What is the structural model of a three-way ANOVA?
Each participant's score is based on: * Grand mean * Main effects of Factors A, B, and C * Two-way interaction effects * Three-way interaction effect * Error/residual
45
What is the purpose of omnibus tests in a three-way ANOVA?
To determine if there are significant main effects or interactions among the factors.
46
True or False: In a three-way ANOVA, two-way interactions are based on comparisons between cell means.
False. They are based on comparisons between a new type of marginal mean, averaging over the third factor.
47
What statistical output is important for interpreting main effects in a three-way ANOVA?
SPSS output that shows SS, df, MS, F, and p-values for each factor.
48
What do follow-up tests in a three-way ANOVA determine?
They help establish the direction and nature of significant main effects and interactions.
49
Fill in the blank: A three-way interaction indicates that the effect of one variable changes at each level of a _______.
[second factor]
50
What do simple interactions in a three-way ANOVA help to analyze?
They help to understand how the effect of one factor on the dependent variable changes depending on the levels of the other two factors.
51
What is the goal when interpreting a three-way interaction?
To understand how the effect of one factor on the dependent variable changes depending on the other two factors.
52
What should be done if any three-way interaction is significant?
Test for simple interactions between two factors at each level of the third factor.
53
What is the significance of the SPSS output for main effect comparisons?
It shows whether participants rate candidates differently based on factors such as attractiveness.
54
What is the goal when interpreting a three-way interaction?
To understand how the effect of one factor on the DV changes depending on the other two factors.
55
What do we test for if any three-way interaction is significant?
Simple interactions between two factors at each level of the third factor.
56
What is the first step in interpreting a three-way interaction?
Break it down into a set of two-way simple interactions at each level of the third factor.
57
True or False: Simple two-way interactions are conducted only if there is a significant three-way interaction.
True.
58
What are the components of the summary table for simple interaction effects?
* Source * SS * df * MS * F * p
59
What is the definition of an omnibus two-way interaction?
Tests the interaction between two factors with data averaged across the third factor.
60
What is the definition of a simple two-way interaction?
Tests the interaction between two factors at each level of the third factor.
61
Fill in the blank: The simple simple effects are the effect of Factor A at each level of Factor B, at each level of _______.
Factor C.
62
What is a simple simple effect?
Effect of Factor A at each level of Factor B, at each level of Factor C.
63
How are degrees of freedom for each simple effect determined?
They are pulled from the omnibus ANOVA for the associated main effect.
64
What is the significance level denoted by p in the summary table?
Indicates the statistical significance of the results for each simple interaction.
65
What does the Univariate Tests table include?
Test results for simple simple effects of candidate attractiveness.
66
What does the Error row in the summary table indicate?
Represents the error variance associated with the tests.
67
Fill in the blank: Degrees of freedom for each simple effect are just the ______ for the associated main effect of the same variable.
df
68
What does a significant simple effect indicate?
There is a significant difference somewhere among the cell means for the levels of that factor.
69
True or False: Significant simple effects can be interpreted without follow-up tests.
False
70
What are simple comparisons used for?
To compare levels of Factor A at each level of Factor B, at each level of Factor C.
71
What is required if there are more than 2 levels of a factor in a significant simple effect?
Follow-up tests
72
What type of tests are used to follow up significant simple effects?
Simple comparisons
73
Why is caution necessary when interpreting main effects qualified by significant interactions?
The main effect may be misleading and change based on the other factor.
74
What are the potential problems with conducting exhaustive follow-up tests?
* Complexity and time consumption * Inflation of familywise error rate * Redundancy of tests * Irrelevance to research questions
75
What should you be cautious about when a main effect is qualified by a significant interaction?
The main effect may be misleading ## Footnote The effect may change based on the other factor, and some researchers may choose not to interpret the main effect at all.
76
What does a significant higher-order interaction require when interpreting a two-way interaction?
It may require you to change the interpretation of the lower-order interaction effect ## Footnote Some researchers may choose not to interpret the two-way interaction in this situation.
77
What is the conclusion regarding the omnibus main effect when comparing groups?
It is misleading: Low < Average = High ## Footnote This indicates that the overall comparison does not accurately reflect the differences among groups.
78
What should you consider when deciding which main effects and lower-order interactions to follow up?
It depends on your research questions and hypotheses ## Footnote If you predict an effect, report it along with relevant follow-up tests.
79
When might follow-up tests not be needed for significant main effects or lower-order interaction effects?
* The effect is peripheral to your research question(s) * The effect is qualified by a higher-order interaction ## Footnote This implies that not all significant results warrant further investigation.
80
What is one strategy for interpreting factorial designs?
Start by interpreting the highest-order interaction and work down from there ## Footnote This includes lower-order interactions and main effects.

PSYC3010 (3 decks)

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