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Split Plot or Mixed Factorial Design

Example. Suppose a perceptual psychologist is interested in age differences in task performance; the target letter is shown at the center of the screen (0 degree), and off-center (4 degrees, 8, and 12 degrees). Specifically, the researcher is interested in determining whether older adults respond di

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Split Plot or Mixed Factorial Design

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    1. Split Plot (or Mixed) Factorial Design At least one Repeated Subjects Factor and at least one Between Subjects Factor

    2. Example Suppose a perceptual psychologist is interested in age differences in task performance; the target letter is shown at the center of the screen (0 degree), and off-center (4 degrees, 8, and 12 degrees). Specifically, the researcher is interested in determining whether older adults respond differently than younger adults. The researcher measures how long it takes each participant to react to the different presentations of the target letters.

    3. Conceptualize the Design What are the independent variable? What are factors and levels? What is dependent variable? Draw box to represent experiment. How would you enter the data in SPSS Data Editor?

    19. Results A 2(age) by 4( position) split plot ANOVA using the multivariate approach to repeated measures on reaction time resulted in a statistically significant interaction (Wilks Lambda F (3, 10) = 7.69, p=.006).

    22. Interaction A significant interaction is followed up with test of simple effects. You can either do repeated measures factor within the between subjects levels (aka like a one-way repeated measures design) or the between subjects factor within each level of repeated measures (Like a oneway between subjects design)

    23. For this Example Makes sense to compare differences in location of stimuli (0, 4, 8, & 12 degrees) for younger adults and then for older adults. So Test of simple effects of degree within age.

    24. Trick Can’t do this test of simple effects the way you did when both factors were between subjects. You need to do it differently

    25. Step 1 Get the computer to see only the younger adults. Under Data choose Select Cases

    31. Now run a oneway repeated measures

    35. Now need to repeat with age=1

    43. Results Continued Simple effect tests of degree within age using a Bonferroni correction of .05/2=.025 showed a significant difference in reaction time among the 4 positions for younger adults (Wilks Lambda F( 3,4)=20.49, p=.007) but not older adults.

    44. Homework Computer Project 2

    45. Other homework Hinkle p. 441-442 #7 only now the same people are tested at each time period (use SPSS to conduct omnibus test)

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