A Two-Way Mixed ANOVA compares the difference between multiple sets of data comprising between-subjects and repeated-measures variables.
It is considered a parametric test and is only suitable for parametric data. To check if your data is parametric, please check out the dedicated guide: Parametric or Not Guide (PDF)
This is one of the most advanced statistical tests that students may need to conduct for their analysis.
Click Analyze > General Linear Model > Repeated Measures
Within the "Repeated-Measures Define Factors" Window, create a name for your repeated-measures factor and specify the number of levels, in my example I have two levels. Click Add. Click Define.
Within the "Repeated Measures" Window, select the dependent variables you are analysing and move them into the "Within-Subjects Variables" box. Then select the grouping variable and move it into the "Between-Subjects Factors" box.
Click "Pst Hoc". Within the "Repeated Measures: Post Hoc Multiple Comparisons for Observed Means" window select your between-subjects factor and move it to the "PostHoc Tests for" window. Select "Bonferroni", click "Continue"
Click "Options". Within the "Repeated Measures: Options" window select "Descriptive Statistics" and "Estimates of effect size".
Select Continue à OK
SPSS will generate a very large number of tables, to correctly report this test we need to select the correct pieces of information from each table. This can be very challenging.
There was a significant main effect of Temperature on animal speeds, F(1,70)=6.10, p = .016, η=.08. Average speeds were significantly higher on hot days (M = 51.71, SD = 14.54) than cold days (M = 49.67, SD = 8.15). There was a significant main effect of animal species on animal speed F(2,70) = 242.97, p < .001, η = .87. Giraffes (M = 64.18, SD = 8.00) were faster than White Rhinos (M = 45.02, SD = 6.03) and African Elephants (M = 42.61, SD = 5.42). There was also a significant interaction effect between temperature and animal species F(2,70) = 35.63, p < .001, η=.50.
In addition, if your ANOVA is significant you must also report your post-hoc results for example:
The difference between Giraffes and White Rhinos, 19.16 95% CI [16.92, 21.40], was statistically significant (p < .001). The difference between White Rhinos and African Elephants, 2.41 95% CI [0.21, 4.61], was statistically significant (p = .032).The difference between Giraffes and African Elephants, 21.57 95% CI[19.47, 23.67], was also statistically significant (p < .001).