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Chapter 8

Chapter 8 - Experimental Design II.docx

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PSYC 2030
Rebecca Jubis

Chapter 8: Experimental Design II - Factorial Designs Factorial Essentials  A factorial design involves any study with more than one independent variable (the terms “independent variable” and “factor” mean the same thing) – factorial designs could have many independent variables but in practice these designs involve two or three factors, sometimes four. Identifying Factorial Designs  A factorial is described with a numbering system that identifies the number of independent variables and the number of levels of each variable, for example, 2 X 3 factorial design has two independent variables – the first has two levels and the second has three OR a 3 X 4 X 5 factorial design has three independent variables, with three, four and five levels.  The total number of conditions to be tested in a factorial study can be identified by looking at all possible combinations of the different levels of each independent variable which produces a factorial matrix – the term “levels” refers to the number of levels of the independent variable whereas the term “conditions” equals the number of cells in a matric, for example, the 2 X 2 memory study has two independent variables, each with two levels and it has four different conditions because of the four cells in the matrix – the number of conditions can be determined by calculating the product of the numbers in the notation system, for example, 3 X 3 design has nine conditions and 2 X 2 X 2 design has eight conditions. Outcomes – Main Effects and Interactions  In factorial studies/designs, two kinds of results occur – main effects and interactions. Main effects refer to the overall influence of the independent variables, and interactions examine whether the variables combine to form a more complex result. Main Effects  In the memory study, the researcher is interested in the effects of two independent variables: type of training and presentation rate – the term main effect is used to describe the overall effect of a single independent variable therefore, in a study with two independent variables, 2 X 2 factorial, there can be at most two significant main effects.  Determining the main effect of one variable or factor involves combining all of the data for each of the levels of that factor – in the memory study, the main effect of type of training is determined by combining the data for those trained to use imagery (for both presentation rates) and comparing it to all of the data for those using rote repetition.  The way to find out if there is a main effect of type of training is to compare all of the “imagery” data with all of the “rote” data – this involves calculating what are called row means and you would calculate column means in order to see if there is a main effect of presentation rate – you would have to conduct ANOVA to see if the differences are statistically significant or simply due to chance. Interactions  In a factorial design, an interaction is said to occur when the effect of one independent variable depends on the level of another independent variable – interactions provide the most interesting results and can sometimes render main effects irrelevant.  For example, comparing course type for general psychology (lecture or lab) and if its true for certain types of students (student’s major – science or humanities) – 2 X 2 factorial design – the dependent variable would be some measure of learning so use a score from 1 to 100 on a standardized test of knowledge of general psychology given during final exam week:  There are no main effects because the row and column means are the same: 75. However, something still happened in the study – the science students did better I the lab course but the humanities student
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