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Chris -

Even if you didn't give me answer I was hoping for, this is excellent information.

Much, much appreciated. You have saved me a lot of time trying to sort this out on my own.

Thank you.

Brian Lucas

Thanks to both of you. Extremely helpful. One remaining issue. Below is the code that I ran successfully with RIGLS based on your advice. As you'll see, this is a two-level random linear trend model. Each constraint define command sets a variance for an aggregated measurement for a particular time p...

Thank you for your response. I am attempting to run a random quadratic trend model with level 2 defined by study_i and level 1 defined by aggregated blood volume measurements across several time points. (Note that, if I had complete individual patient data, this could be a 3 level model with level 3...

Users - I am conducting a 'longtitudinal' or 'repeated measures' meta-analysis. Using summary data from multiple studies, my goal is to determine an estimate of the quadratic change in a continuous variable (blood volume) over time. The observations I have from each study contain 3 variables: 1. tim...

George - I confirmed that I have the most recent version of runmlwin. Below I have pasted my syntax for the ordinal model (outcome takes values 0, 1, 2) with a non-hierarchical structure (aid and resident are crossed) using uniform random effects priors. I follow this syntax with 2 commands: "r...

I have noticed a minor issue with the mode and median options - both reporting options for the MCMC mode. When I use either option the column header for the random effects is appropriate - "mode" or "median", respectively. But in both cases the column header for the fixed effects...

George - Thanks for the quick response. I should have mentioned my reason for using likelihood-based methods. There are 2 reasons. First, I want better starting values for MCMC. When I attempt to fit my models using MCMC, I have computational problems. For example, I get the following message "...

I am trying to estimate a cross-classified random intercepts ordered multinomial model with common coefficients for predictor variables. Although I found no examples of such a model, I am assuming that MLwiN can run such models. (I know that MLwiN can run a cross-classified random intercepts binomia...