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Exam 4 - Chapter 12 Designing Conducting Analyzing and...

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Chapter 12 – Designing, Conducting, Analyzing, and Interpreting Experiments with Multiple Independent Variables Factorial Designs Factors = IV Allow us to look at combinations of IVs at the same time At least 2 IVs in order to have factorial design o More practical and most common are 2 or 3 levels 2 X 2 – doubling of our basic 2 level, one IV design from Ch. 10, 11 How many numbers? 2 X 2 X 3 (3 IVs) Value of numbers – 2 levels X 2 levels X 3 levels 2 X 2 = 4 treatment conditions, 2 X 3 = 6 treatment conditions o Multiply get number of treatment conditions If you don’t use a factorial design and separate into smaller studies you will lose time efficiency and the interaction Make sure the IVs go together o Self esteem and eye color doesn’t go with test performance Consider control issues; repeated measures gives us greater confidence that there is equality in our groups when we don’t have 10 Ss per group Keep it simple stupid (KISS); don’t make more complicated than it needs to be ( principles of parsimony ) o More Ss required, more experimental conditions, more chances things can go wrong Data interpretation becomes nearly impossible with 4, 5, 6 IVs; most people use 2 or 3 Adding levels into factorial design increases groups in multiplicative fashion o 2 X 2 X 2 = 8 conditions, 3 X 2 X 2 = 12 conditions Ex post facto – only way to study sex, personality, race, etc. ( IV cannot be directly manipulated ) Assigning Participants to Groups Random assignment o IVs involve random assignment ( between-subjects factorial designs or completely randomized designs ) Independent groups – groups of participants formed by random assignment Correlated groups – groups of participants formed by matching, natural pairs, or repeated measures Completely within-groups (or within-subjects) designs o Correlated assignment in order to assure the equality of participant groups o Nonrandom assignment to groups Matched pairs or sets The more levels an IV has, the more work matching for that variable takes, simply because of having to form larger sets of participants that are equated on the matching variable. Repeated measures Natural pairs or sets
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Mixed assignment o Involve a combination of random and correlated assignment, with at least one IV using each type of assignment to groups o The use of repeated measures is probably more likely than other types of correlated assignment Main effects and Interactions Main effect o Looking at result of each IV separately on the DV. o Refers to the sole effect of one IV in a factorial design Interaction o Exists when one IV depends on particular level of another IV o Crossing lines or lines that converge typically suggest an interaction; parallel lines always equals no interaction o The joint, simultaneous effect on the DV of more than one IV o We find significant interactions when the effects of one IV change as the level(s) of the other changes.
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