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Guidelines for IDing Experimental Design Levels/ participant? One Independent Groups design More than one Repeated Measures design Once: incomplete Yes:

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Presentation on theme: "Guidelines for IDing Experimental Design Levels/ participant? One Independent Groups design More than one Repeated Measures design Once: incomplete Yes:"— Presentation transcript:

1 Guidelines for IDing Experimental Design Levels/ participant? One Independent Groups design More than one Repeated Measures design Once: incomplete Yes: all possible orders No: selected orders Four or fewer conditions? More than once: complete Yes: block randomization No: ABBA counterbalancing Anticipation problems? Times each level/ Participant?

2 Complex Designs When a two-way is more than spaghetti and chili!

3 What are they? Simple versus complex designs –One-way versus Two-way, etc. Types of factorial designs –Completely randomized –Completely within –Mixed Variable and level shorthand 2 x 2 2 x 3 2 x 2 x 3

4 What good are they? Advantages of complex designs Economy Understanding External validityinteractions Example: social facilitation versus evaluation apprehension

5 Some Data

6 Identifying Main Effects and Interactions Interpretation –Main effects: the overall effect of one independent variable on the dependent variable. –Interactive effects: the effect of the first independent variable on the dependent variable that is contingent on a particular level of the second independent variable. ordinal interactions disordinal (crossover) interactions

7 Analysis of Complex Designs Simplest case: the 2 x 2 design –Three classes of scientific hypotheses Main effect of treatment method: e.g., behavioral method will be more effective than the cognitive method Main effect of presenting problem: e.g., treatment will be more effective for habit problems than learning problems Interaction effect of treatment method x presenting problem: e.g., cognitive therapy will be more effective for learning problems, but behavioral therapy will be more effective for habit problems

8 Interactions: Looking at the picture…

9 Analysis: When Interaction is Present… Evaluate evidence descriptively –Graphs (non-parallel lines) –Tables (subtraction method) Confirm by inferential statistics: complex ANOVA Qualifies our interpretation of the main effect

10 Analysis: When Interaction is NOT present… Focus is on interpreting the main effect(s) Analytical comparisons of the marginal means and confidence intervals with planned comparisons

11 The many faces of 2 x 2s: Possible Results #1 What do we have here?

12 The many faces of 2 x 2s: Possible Results #2 What do we have here?

13 The many faces of 2 x 2s: Possible Results #3 What do we have here?

14 The many faces of 2 x 2s: Possible Results #4 What do we have here?

15 The many faces of 2 x 2s: Possible Results #5 What do we have here?

16 The many faces of 2 x 2s: Possible Results #6 What do we have here?

17 The many faces of 2 x 2s: Possible Results #7 What do we have here?

18 The many faces of 2 x 2s: Possible Results #8 What do we have here?

19 Interpreting Interactions Theory testing External validity Ceiling and floor effects Natural groups design


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