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SM0269 Global And International Business Contexts

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Question:

Our first inferential statistic we will use is a t-test as a review of what you learned in Week 6.  We want to compare pre-treatment scores to post-treatment scores (we are going to collapse across the treatments to see whether there is an overall change in all people).
t-test
Run a repeated measures t-test (also known as a paired-sample t-test) to determine whether there is a overall change between pre and follow-up PTSD symptoms 
Click on ANALYZE/COMPARE MEANS/PAIRED SAMPLES t-test
In the dialog box, we will first click on ‘pre’ then on ‘followup’ (below the variables, there is a box that is labeled current selections)
move the paired variables to the PAIRED VARIABLES box
Q1) For this analysis, what is H0:
 
Q2) Based on the paired t-test results, what can you say about an overall treatment effect? Do people get better over time? Make sure you use the APA notation when describing the statistics (e.g., A significant effect was found for… (t (23) = 2.97, p < .05); ASK in the discussion if you are unsure how to do this.).
 
 
 
One-Way ANOVA
Our first ANOVA will be comparing the 3 exercise groups on the last time point.  We want to see whether the exercise groups have a different amount of PTSD at followup (one month after treatment).  Participants reported different amounts of exercise (low, medium, and high), so we are interested in whether there was a difference for the three exercise groups. 

Q3) Write the H0: for the ANOVA comparing 3 groups at follow up
 
 

?Click on ANALYZE/COMPARE MEANS/ONE-WAY ANOVA
?In the dialog box:
oour dependent variable is ‘followup’
oour factor is ‘exercise’
?We can also get a graph of the means of our groups, if we click on OPTIONS and then MEANS PLOT in the next dialog box (note: it is interesting to see how SPSS will automatically generate the y-axis range according to the data, this feature can make a nonsignificant result look significant and a significant result look nonsignificant depending on your data).  
?We can also compute post-hoc differences to determine which of the groups, if any, differ significantly. Click on Post-hoc and check the box next to Tukey.
?Click on OK

Q4) What can you say about the groups one month after treatment (at followup)? Make sure you use the APA notation when describing the statistics (e.g., A significant effect was found for… (F (1, 23) = 2.97, p < .05); ASK in the discussion if you are unsure how to do this.).
 
 
 
Q5) Is there a need to do Post Hoc tests (i.e., do we have an overall difference between groups, where we will need to find which individual groups are different)? If so, report which groups differ significantly from each other, along with the significance level (p value).
 
 
 
Two-way ANOVA
The main advantage of a factorial ANOVA is that we get to see the two IVs interacting. Thus, we want to run an analysis where we get the interaction term.  
Let’s say we are looking at the followup PTSD scores, and want to determine whether the reduction in PTSD severity is due to the amount of exercise they reported or therapy condition to which they were assigned. 
Run an ANOVA on TherapyGroup and Exercise
ANALYZE>GENERAL LINEAR MODEL>UNIVARIATE
Place followup in the DEPENDENT VARIABLE box
Place therapygroup AND exercise in the FIXED FACTORS box
Plots are very important when looking at interactions.  Whenever we see plots where the lines are not parallel or they cross, we can be pretty sure we have an interaction.  We can plot this data in two different ways (both plots will give us the same information, but in different formats). For the first plot, click on PLOT and put therapygroup in HORIZONTAL AXIS and exercise in SEPARATE LINES, then click ADD and CONTINUE)
For the second plot, click on PLOT and put exercise in HORIZONTAL AXIS and group in SEPARATE LINES, then click ADD and CONTINUE)
There is a lot of output presented.  We can look at the main effect of group and exercise.  However, in factorial ANOVA, we MUST interpret the interaction first.  If there is a significant interaction, then there is no reason to look at the main effects.  That is, the interaction is the only thing that is interesting (if it is significant).  
The interaction is listed as therapygroup*exercise in the “Test of Between-Subject Effects” table.  

Q6) Is there a significant interaction effect of group and exercise on PTSD scores at follow up? Make sure you use the APA notation when describing the statistics (e.g., A significant interaction effect was found for… (F (1, 23) = 2.97, p < .05).).
 
Q7) Based on the first plot where you have separate lines for exercise, what do you see is happening for the different levels of exercise? 

Q8) Based on the second plot where you have separate lines for group, what do you see is happening for the different levels of therapygroup?
 
Q9) Is there a significant main effect of therapy group on PTSD scores at follow up? Make sure you use the APA notation when describing the statistics (e.g., A significant interaction effect was found for… (F (1, 23) = 2.97, p < .05).).

Q10) Is there a significant main effect of exercise on PTSD scores at follow up? Make sure you use the APA notation when describing the statistics (e.g., A significant interaction effect was found for… (F (1, 23) = 2.97, p < .05).). Is this similar to or different from the results of the one-way ANOVA? How so?  
 
Q11) Write up the results as if you were writing up a results section. Describe what you have found so far in your study. Here are some pointers on what to include: 
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