I plan to conduct a study where each participant is randomly exposed to two different stimuli (audio and visual stimuli) in total 180 clips. The stimuli contain 10 different levels with corresponding ratings of 2 different scales (0-10). I will also calculate which of the scales are used in order to see if the participant chose the two correct scales (out of possible 5). I will calculate the main effects and interaction effects and not sure which analysis fits best. I know that LMM is best for missing data, but besides that are there other advantages of this type of analysis? I would like to keep it as simple as possible.
Maybe you have some experiences that you would like to share. Thank you for your help in advance :)
Why do you think it is a mixed (fixed and random) model - what is it that is being repeatedly measured ? This may help: http://www.bristol.ac.uk/cmm/software/mlwin/mlwin-resources.html#mlmbkgrd
Thanks for the link, I am still not sure which model is best for the current study. I will measure emotion recognition accuracy and also intensity (0-10 scale) repeatedly with the same emotion but expressed through different actors. There will be 180 measures and ten different emotions so each emotion will be measured 18 times within 60 minutes. Emotion ratings will be my dependent variable and I assumed the two modalities are fixed.
Article Categorical Data Analysis: Away from ANOVAs (transformation ...
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