Reportinga split plot anova

1. Reporting a Split-Plot ANOVA in
SPSS
Amit Sharma
Associate Professor
Dept. of Pharmacy Practice
ISF COLLEGE OF PHARMACY
Ghal Kalan, Ferozpur GT Road, MOGA, 142001, Punjab
Mobile: 09646755140, 09418783145
Phone: No. 01636-650150, 650151
Website: - www.isfcp.org

2. Note –

3. Note – the reporting format shown in this
learning module is for APA. For other formats,
consult specific format guides.

4. Note – the reporting format shown in this
learning module is for APA. For other formats,
consult specific format guides. It is also
recommended to consult the latest APA manual
to compare what is described in this learning
module with the most updated formats for APA.

5. A typical example of a split-plot analysis report
might be:

6. A typical example of a split-plot analysis report
might be: “The main effect of Gender was
significant, F(1, 19) = 7.91, MSE = 23.20, p <
0.01, as was the main effect of Time, F(3, 19) =
12.70, MSE = 23.20, p < 0.01. The interaction of
these two factors was not significant, F(3, 19) =
2.71, MSE = 23.20, n.s.”

7. Let’s break this down:

8. Let’s break this down: “The main effect of
Gender was significant, F(1, 19) = 7.91, MSE =
23.20, p < 0.01, as was the main effect of Time,
F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The
interaction of these two factors was not
significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”

9. Let’s break this down: “The main effect of
Gender was significant, F(1, 19) = 7.91, MSE =
23.20, p < 0.01, as was the main effect of Time,
F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The
interaction of these two factors was not
significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”
This is the F ratio for the 1st
main effect. We compare
this value with the F critical.
If the F ratio is greater than
the F critical then we would
reject the null hypothesis.

10. Let’s break this down: “The main effect of
Gender was significant, F(1, 19) = 7.91, MSE =
23.20, p < 0.01, as was the main effect of Time,
F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The
interaction of these two factors was not
significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”
This is the degrees of freedom for gender
- 2 levels (female & male) - 1 = 1.

11. Let’s break this down: “The main effect of
Gender was significant, F(1, 19) = 7.91, MSE =
23.20, p < 0.01, as was the main effect of Time,
F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The
interaction of these two factors was not
significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”
This is the degrees of
freedom for error value.

12. Let’s break this down: “The main effect of
Gender was significant, F(1, 19) = 7.91, MSE =
23.20, p < 0.01, as was the main effect of Time,
F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The
interaction of these two factors was not
significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”
This is the F ratio for the 2nd
main effect

13. Let’s break this down: “The main effect of
Gender was significant, F(1, 19) = 7.91, MSE =
23.20, p < 0.01, as was the main effect of Time,
F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The
interaction of these two factors was not
significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”
This is the Mean Square
for the Error Value

14. Let’s break this down: “The main effect of
Gender was significant, F(1, 19) = 7.91, MSE =
23.20, p < 0.01, as was the main effect of Time,
F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The
interaction of these two factors was not
significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”
This is the p value indicating
that result was statistically
significant.

15. Let’s break this down: “The main effect of
Gender was significant, F(1, 19) = 7.91, MSE =
23.20, p < 0.01, as was the main effect of Time,
F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The
interaction of these two factors was not
significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”
F ratio or value for the 2nd
main effect

16. Let’s break this down: “The main effect of
Gender was significant, F(1, 19) = 7.91, MSE =
23.20, p < 0.01, as was the main effect of Time,
F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The
interaction of these two factors was not
significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”
Degrees of freedom for 4
levels of time (4-1 = 3)

17. Let’s break this down: “The main effect of
Gender was significant, F(1, 19) = 7.91, MSE =
23.20, p < 0.01, as was the main effect of Time,
F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The
interaction of these two factors was not
significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”
Degrees of freedom for
the error value.

18. Let’s break this down: “The main effect of
Gender was significant, F(1, 19) = 7.91, MSE =
23.20, p < 0.01, as was the main effect of Time,
F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The
interaction of these two factors was not
significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”
This is the F ratio for the
2nd main effect

19. Let’s break this down: “The main effect of
Gender was significant, F(1, 19) = 7.91, MSE =
23.20, p < 0.01, as was the main effect of Time,
F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The
interaction of these two factors was not
significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”
This is the Mean Square for
the Error Value

20. Let’s break this down: “The main effect of
Gender was significant, F(1, 19) = 7.91, MSE =
23.20, p < 0.01, as was the main effect of Time,
F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The
interaction of these two factors was not
significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”
This is the p value indicating that
result of the 2nd main effect was
statistically significant.

21. Let’s break this down: “The main effect of
Gender was significant, F(1, 19) = 7.91, MSE =
23.20, p < 0.01, as was the main effect of Time,
F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The
interaction of these two factors was not
significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”
F ratio or value for the
interaction effect

22. Let’s break this down: “The main effect of
Gender was significant, F(1, 19) = 7.91, MSE =
23.20, p < 0.01, as was the main effect of Time,
F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The
interaction of these two factors was not
significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”
Degrees of freedom for (2-1=1)
levels of gender TIMES (4-1=3)
EQUALS 3 time X

23. Let’s break this down: “The main effect of
Gender was significant, F(1, 19) = 7.91, MSE =
23.20, p < 0.01, as was the main effect of Time,
F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The
interaction of these two factors was not
significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”
Degrees of freedom for
the error value.

24. Let’s break this down: “The main effect of
Gender was significant, F(1, 19) = 7.91, MSE =
23.20, p < 0.01, as was the main effect of Time,
F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The
interaction of these two factors was not
significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”
This is the F ratio for the
interaction effect

25. Let’s break this down: “The main effect of
Gender was significant, F(1, 19) = 7.91, MSE =
23.20, p < 0.01, as was the main effect of Time,
F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The
interaction of these two factors was not
significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”
This is the Mean Square
for the Error Value

26. Let’s break this down: “The main effect of
Gender was significant, F(1, 19) = 7.91, MSE =
23.20, p < 0.01, as was the main effect of Time,
F(3, 19) = 12.70, MSE = 23.20, p < 0.01. The
interaction of these two factors was not
significant, F(3, 19) = 2.71, MSE = 23.20, n.s.”
This means that the
result is not significant.