1. Post Hoc or Multiple Comparison Testing
To determine which group means are statistically different
Ideally, should test just what groups you want to compare – particularly if small sample size
Select type of post hoc testing (eg, Tukey, Bonferroni, Scheffe) based on variance assumptions and how many comparisons are needed
** cannot just do multiple t-tests because it increases the risk of Type I error **

2. Examples: One-Way ANOVA
Research Question: Is there a difference in confidence scores among those who are rarely, sometimes or often in a depressed state of mind?

3. Mean (SD) Confidence Score
Depression Level N
Mean (SD) Confidence Score
F-Ratio and p-value
Multiple Comparisons   
Rarely Sometimes
Rarely
356
68.89(10.05)
F = (p=.001)
Sometimes
266
58.22(10.83)
p  = .001
Often 47
46.23(12.50)
p = .001
Interpretation
There is a statistically significant difference in overall confidence score between depression groups F(3, 676) = , p <.001.
The post hoc testing indicated that there was a significant difference in confidence scores between those who were rarely depressed and all of the other groups The group that is rarely depressed rated their confidence score (mean = 68.89) significantly higher than the sometimes (mean = 58.22) and often (mean = 46.23) groups.

4. Mean (SD) Confidence Score
Depression Level N
Mean (SD) Confidence Score
F-Ratio and p-value
Multiple Comparisons   
Rarely Sometimes
Rarely
356
68.89(10.05)
F = (p=.001)
Sometimes
266
58.22(10.83)
p  = .001
Often 47
46.23(12.50)
p = .001
Which of the following conclusions can be made based on the above data?
A. There is a not a significant difference between the depression levels.
B. The sometimes group reported a significantly higher mean confidence score as compared to the often group.
C. The sometimes group reported a significantly lower mean confidence score as compared to the often group.
D. There is not a significant difference between the mean confidence scores of the rarely and sometimes groups.

5. Mean (SD) Job Satisfaction Score F-Ratio and p-value
Nursing Staff N
Mean (SD) Job Satisfaction Score
F-Ratio and p-value
MultipleComparisons     RN             LPN RN 20
45.0(3.95)
F = (p=.001)
LPN
41.7(5.79)
p  = .258
UAP
36.2(6.37)
p  = .024
p = .004
Levene’s Test = .526
1.We see that the mean job satisfaction score for the RN group is 45.0 (SD 3.95), the LPN group is 41.7 (SD 5.79) and the UAP group is 36.2 (SD 6.37).
2. Levene’s test result=.526 which is not significant because p>.05 so we can assume that there is no significant difference between the variances of the two groups.
3.The next value is the F-ratio which is and the p-value corresponding to the F-ratio is Since the p-value is <.05 (p=.001) we can reject the null hypothesis.
4. The next step is to determine where the differences exist among the groups (i.e., RN vs. LPN, RN vs. UAP, LPN vs. UAP).
RNs to LPNs – the value for p=.258 which is greater than .05, which means it is not significant, and you conclude that there is no difference in the mean job satisfaction scores of RNs vs. LPNs (45.0 and 41.7 respectively).
RNs to UAPs – the value for p=.024 whichis less than .05, which means it is significant, and you conclude that there is a statistically significant difference in the mean job satisfaction scores of RNs vs. UAPs (45.0 and 36.2)
LPNs to UAPs – the value for p=.004 which is less than .05, which means it is significant
In conclusion, the UAPs are less satisfied than both the RNs and LPNs.