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Hi Is there any way to fit a bivaraite longitudinal mixed model using R. I have a data set with col names resp1 (Y_ij1), resp2 (Y_ij2), timepts (t_ij), unit(i) j=1,2,..,m and i=1,2,..n. I want to fit the following two models Model 1 Y_ij1, Y_ij2 | U_i = u_i ~ N(alpha + u_i + beta1*t_ij, Sigma) U_i ~ iid N(0, sigu^2) Sigma = bivariate AR structure alpha and beta are vectors of order 2. Model 2 Y_ij, Y_ij2 | U_i = u_i ~ N(alpha + u_i +...

...ist posting this here. I have a problem where each participant is shown a series of visual cues (displayed on a computer screen in a random order) and asked to respond by pressing a button (from a finite number of buttons) that corresponds to the correct answer. The data is of the form (r_ij , t_ij), where r_ij = 1 indicates correct response by the i-th subject on the j-th cue, and t_ij is the time taken to respond. Are there statistical models to describe this set up? Any references or suggestions would be greatly appreciated. Thanks very much, Ravi. [[alternative HTML version dele...

Hi everyone, I want to fit the following mixed effect model Y_ij = b_0i + b_1i * (t_ij*grp_ij == 1) + b_2i * (t_ij*grp_ij == 2) + v_0i + v_1i*t_ij + e_ij with a different covariance matrix of random effects for each group. (Y is the response t is time grp is the group indicator b 's are fixed effects v 's are random effects) I know that this is possible in SA...