[R-lang] lmer-random slopes with unique items across conditions

[linda]

    Dear members of the ling-r-lang-L mailinglist,

          

        at the moment I am changing
              the lmer-analyses on my eye tracking data, and I facing
              one major problem. I hope you can help me by answering
              this questions.

              

              I conducted an eye tracking study in which children read
              an very easy (below grade level) and a more difficult text
              (above grade level). The design is presented below.

              

              Grade --- Below
              - Above 

              -----------------------------

              Grade 3---Text A- Text B

              Grade 5----Text B- Text C

            

            All words within the text
            were included in the analyses. Word frequency, word length,
            Working Memory capacity, decoding skills and reading
            comprehension were included as fixed effects. Since the
            children in the different grades did not read the same texts
            (only text B was presented to all participants), the words
            (items) were not identical across conditions. Hence, it is
            difficult to include item as a random variable and I first
            ran an analyses based on data that was aggregated by subject
            and included only subject as a random variable. 

            Off course, the problem of making a Type I error inherently
            increases. 

            

            I figured that, in order to included item as a random
            variable, I could make unique variable numbers across texts.
            This would, I assume, explain variance of random effects
            caused by a specific word/item, but not explain random
            slopes across conditions (as itemnr is unqiue across
            conditions). One major question is, that am not sure how
            lmer estimates the random slopes now. There are a lot of
            missings for each participants (about 152 items are missing
            for each participant) since measurements are only available
            for two out of three texts for each participant. Is lmer
            able to estimate random slopes when have missing values. And
            is it a good idea to include item as a random variable here,
            or is it better to continue working on the aggregated data?

        
    -- 

        Kind regards,

      
      

        Linda de Leeuw

      
      

      
  


 		 	   		  
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