Two factor Independent-measures ANOVA -
The study is a two-factor design examining the effects of two treatment conditions on males and females. Gender (male vs female) is one factor (defined as Factor A in the problem) and this is a between subjects factor (because there are different people in these categories). Treatment is a second factor (defined as Factor B in the problem) and this is also a between subjects factor (because there are different groups of people in each of the two treatment categories. Thus, you have four completely separate groups of people in this study. Further, n=4 for each of the four groups. Note how the data are entered here. In the gender grouping variable (the first grouping variable), you list all of one group and then all of the other. For the next, you alternate between conditions. This always has to be true.
Problem - Here is an output box from another example that contains the Tukey post-hoc test results. This box is saying that groups 1 and 2 are NOT different, because the Sig. is 0.584 (way above 0.05). Further, conditions 2 and 3 are not different either, because the sig. is 0.134 (closer to 0.05 but still not significant).
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Multiple Comparisons
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Score - Tukey HSD
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(I) dose
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(J) dose
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Mean Difference (I-J)
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Std. Error
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Sig.
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95% Confidence Interval
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Lower Bound
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Upper Bound
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1.00
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2.00
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-1.0000
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1.00000
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.584
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-3.4973
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1.4973
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3.00
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1.0000
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1.00000
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.584
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-1.4973
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3.4973
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2.00
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1.00
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1.0000
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1.00000
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.584
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-1.4973
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3.4973
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3.00
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2.0000
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1.00000
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.134
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-.4973
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4.4973
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3.00
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1.00
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-1.0000
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1.00000
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.584
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-3.4973
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1.4973
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2.00
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-2.0000
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1.00000
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.134
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-4.4973
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.4973
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Based on observed means.
The error term is Mean Square(Error) = 5.000.
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Answer the questions below about this scenario.
The following data are from a study examining the effect of various therapies on duration of sleep in insomniacs. Three different treatment conditions were used, including a control condition (no treatment), Cognitive Behavioral Therapy group, and stimulus control group. The study measured the average number of hours slept for males and females.
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No treatment
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CBT
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Stimulus control
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Males
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4,4,4,6,5
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7,8,9,8,7
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10,9,8,9,10
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Females
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3,5,5,6,4
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6,7,9,8,8
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9,8,9,10,10
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1. Factor A has k=2 and is _________
a. Gender
b. Treatment
c. An interaction
2. Gender is _________________ factor.
a. an independent
b. a repeated measures
3. Treatment is _________________ factor.
a. an independent
b. a repeated measures
4. According to the SPSS output, is there a main effect of Gender (that is, is the factor 'Gender' significant)?
a. Yes
b. No
5. The F-statement F (2,24) = 0.36, p > 0.05 corresponds to:
a. Gender
b. Treatment condition
c. The interaction between the two factors
6. Tukey post-hoc tests tell you that group 1 is different from:
a. Only group 2
b. Only group 3
c. Groups 2 and 3
d. Neither group 2 or 3
Attachment:- Assignment.rar