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...r effect" applies to only one year. One can think of the first score on the student as a score from a prior year (for which I have no teacher links), and the second score is from the current year and is linked to the teacher. The model for student j in class i is: Y_{ij0} = a_0 + e_{ij0} Y_{ij1} = a_1 + b_i + e_{ij1} with Var(b_i) the teacher variance component and Cov(e_{ij0},e_{ij1}) unstructured. That is, if the data are organized by student, the "Z" matrix in the usual linear mixed model notation has every other row equal to a row of zeros. I am wondering whether there is...

...is latent reponse will never be observerd. G_{ij} has a logistic distribution with: Q_{ijk} = P(G_{ij} <= \alpha_{ik}) = 1/(1+exp(-(\alpha_{ik}+\beta*x_{ij}) (k=1,...,m-1) in which Q_{ijk} is the probabilty of having a response for the j-th subject in category k or better that means p_{ij1}+....+p_{ijk}= Q_{ijk} and Q_{ijm}=1, Q_{ij1}=1. i = 1,...,r (r=5) #number of studies j = 1,....,n_{i} #subject j from study i k = 1,...,m (m=5)#Category My problem is how to fit this model in R although I have a SAS code from Whitehead which is availabe at http://www.rdg.ac.uk/mps/mp...