# PSYC 2530 Chapter Notes - Chapter 14: Repeated Measures Design, Analysis Of Variance

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Ch. 14 - Two-Factor ANOVA

Tuesday, November 13, 2012

9:21 PM

PSYC 2530 Introductory Statistics

Chapter 14: Two-Factor Analysis of Variance (Independent Measures)

The mean differences among the levels of one factor are referred to as the main

effect of that factor. When the design of the research study is represented as a

matrix with one factor determining the rows and the second factor determining

the columns, then the mean differences among the rows describe the mean effect

of one factor, and the mean differences among the columns describe the main

effect for the second factor.

Hypotheses for Two-Factor ANOVA:

o

There is no interaction between factors A

and B. All of the mean differences

between treatment conditions are

explained by the main effects of the two

factors.

There is an interaction between factors.

The mean differences between treatment

conditions are not what would be

predicted from the overall main effects of

the two factors.

Interactions

o An interaction between two factors occurs whenever the mean differences

between individual treatment conditions, or cells, are different from what

would be predicted from the overall main effects of the factors.

o When the effect of one factor depends on the different levels of a second

factor, then there is an interaction between the factors.

o When the results of a two-factor study are presented in a graph, the existence

of nonparallel lines (lines that cross or converge) indicated an interaction

between the two factors.