Flashcards in Two-Way Analysis of Variance Deck (15)

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1

## With a two-way analysis of variance (two-way ANOVA)...

### each participant must have scores on three variables: two factors and a dependent variable.

2

## Each factor divides cases into...

### two or more levels, while the dependent variable describes cases on a quantitative dimension.

3

## F tests are performed on the...

### main effects for the two factors and the interaction between the two factors.

4

## Follow-up tests may be conducted to assess...

### specific hypotheses if main effect tests, interaction tests, or both are significant.

5

##
We can analyze data from different types of studies by using two-way ANOVA.

###
Experimental studies

Quasi-experimental studies

Field studies

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## First Main Effect:

###
Are the population means on the dependent variable the same among levels of the first factor averaging across levels of the second factor?

7

## Second Main Effect:

###
Are the population means on the dependent variable the same among levels of the second factor averaging across levels of the first factor?

8

## Interaction Effect:

### Are the differences in the population means on the dependent variable among levels of the first factor the same across levels of the second factor?

9

##
If one or more of the overall effects are significant:

### various follow-up tests can be conducted. The choice of which follow-up procedure to conduct depends on which effects are significant.

10

## If the interaction effect is significant:

### follow-up tests can be conducted to evaluate simple main effects, interaction comparisons, or both. The choice among tests depends on which best addresses the research questions.

11

## If the interaction effect is not significant:

### the focus switches to the main effects. If a main effect for a factor with more than two levels is significant, then follow-up tests can be conducted. These tests evaluate whether there are differences in the means among the levels of one factor averaged across levels of the other factor. These follow-up tests most often involve comparing means for pairs of levels of the factor associated with the significant main effect.

12

## Assumption 1:

### The Dependent Variable Is Normally Distributed for Each of the Populations

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## Assumption 2:

### The Population Variances of the Dependent Variable Are the Same for All Cells

14

## Assumption 3:

### The Cases Represent Random Samples from the Populations, and the Scores on the Dependent Variable Are Independent of Each Other (The two-way ANOVA yields inaccurate p values if the independence assumption is violated.)

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