How to analyse reading data with two word types and three types of dependent variables? In my study, I have one group encoding 2 different types of words (within subjects) and 3 different dependent measures namely recall, recognition, rating. 
I think that I can conduct repeated measure analysis.
But I am confused about what should I write for factor name. I think I have one factor with two levels because all subjects encoded 2 different types of words in the same list.
Is that right?
And I defined three measure names to define DVs.Is that OK?
 A: Without knowing more, it sounds like:


*

*You could perform three separate paired-samples t-tests (IV = encoding condition), one for each of the types of dependent variables.

*If recall, recognition, and rating are all on the same scale, then you could perform a $2 \times 3$ within subjects ANOVA. I can imagine that recall and recognition would both be accuracy measures, but you don't make clear what "rating" represents. I imagine it would be on a different scale and as such it would not make sense to combine it in an overall analysis with recognition and recall.

A: If you have both recall and recognition data from a word list, you may be able to use a multinomial processing tree model, specifically the Chechile-Meyer model. But this depends on your exact design. 
The Chechile-Meyer Task separates storage and retrieval processes in an elegant way. See the following publications:


*

*Chechile, R. A. (2004). New multinomial models for the Chechile–Meyer
task. Journal of Mathematical Psychology, 48(6), 364–384.
doi:10.1016/j.jmp.2004.09.002

*Chechile, R. A. (2010). Modeling
storage and retrieval processes with clinical populations with
applications examining alcohol-induced amnesia and Korsakoff amnesia.
Journal of Mathematical Psychology, 54(1), 150–166. doi:10.1016/j.jmp.2009.03.006


To fit the model, you could use our R package MPTinR (on CRAN), see:


*

*Singmann, H., & Kellen, D. (in press). MPTinR: Analysis of
Multinomial Processing Tree Models in R. Behavior Research Methods.

