# Mixed design anova assumptions

What are the assumptions that I need to consider when running a mixed design ANVOA? Let's say I have the following data set:

                 |       Scenario 1       |     Scenario 2         |
|Trial 1|Trial 2| Trial 3|Trial 1|Trial 2| Trial 3|
-------------------------------------------------------------------
S1 | ...
Condition 1  S2 | ...
S3 |
-------------------------------------------------------------------
S5 |
Condition 2  S6 |
S7 |


Where Condition x is the between-subject variable, S1, S2, ... are the subjects, and Scenarios are within-subject variables, where each Scenario has some nested Trials.

Using lmer I can describe this model by: lmer(value~Condition*Scenario + (1+Scenario|Player) + (1|Scenario/Trial).

Taking a more traditional approach I can collapse over Trials so I have the a mean value for each Scenario.

I think I should do the following:

1. I should check Homoskedasticity per Scenario/Trial
2. Check for the absence of influential data points

Is there something I am missing?

• I do not think that Heteroskedasticity has anything to do with ANOVA – Subhash C. Davar May 22 '14 at 15:01
• I was following Bodo Winter's tutorial. – Pio May 22 '14 at 16:19