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FACTORIAL DESIGNS AND INTERACTION EFFECTS The term “factorial design” conveys two ideas: There is more than one factor (independent variable or grouping variable) in the research design. Data is collected under all possible combinations of the levels of these factors. This means that it is useful to organize data in a matrix of rows and columns. Why Factorial Designs? Two Reasons investigate the effects of factors in combination solve some problems of confounding Varieties of Factorial Design how many factors, and how many levels of each? e.g. 2 x 2; 4 x 6; 2 x 4 x 5; 3 x 3 x 3 x 3; etc o the numbers represent how many levels for each factor are the factors between-subjects or within-subject? e.g. all between; all within; mixed o for each of these factorial designs, there is an analysis of variance o e.g. two between factors and one within
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Example of a 2 x 2 Factorial Design Factor 1: Task Difficulty Easy Difficult Average Morning 93 83 88 Factor 2: Time of Day Afternoon 87 67 77
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