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Hi there, I am trying to run a three-level logistic growth curve model. For some reason this works fine for one outcome (health_bin) but not for another (Kess_bin) Using the following syntax I obtain the following model output for binary-self-rated health: runmlwin health_bin cons E_D E_E W_A W_D S_...

Hi Chris, Thanks for your reply. I had assumed that runmlwin was already installed in the secure environment but it looks like it's not, and I don't have the privileges to do so myself. I'll ask the data holders to install it and upgrade to a newer version of MLwiN and hopefully that will do the tri...

Hi there, I am using MLwiN in the Secure Data environment but I am having trouble using runmlwin. I have specified the MLwiN file path using the 'global MLwiN_path' command but when I try to use the runmlwin command I receive the error message 'unrecognized command: runmlwin’. I'm not sure why this ...

Hi Chris,
Thanks for your response, that's cleared up my confusion,
Elisabeth

Hi there, I am running three-level growth curve models and receiving the error message "WARNING: IGLS algorithm failed to converge. Increase the number of iterations. See the maxiterations() option." I'm not sure why this is happening because I have set the maximum iterations to be 16000 u...

Hi George,
Thank you so much for your help, I've done as you suggest and it works perfectly.
Elisabeth

Hi George,
Thank you very much for the advice and reference. Is it possible to supply syntax to calculate the VPC with random effects of the constant and age? This is not included in the runmlwin journal article so I'm struggling with how to calculate this.
Many thanks,
Elisabeth

Hi there, I am running a three-level growth curve with a random slope of age. I'm unsure whether the VPC should contain just the variance around the constant terms at each level, as follows: display [RP2]var(cons)/([RP3]var(cons) + [RP2]var(cons) + [RP1]var(cons)) But should the random slope at leve...

Thank you George, that's much appreciated.
Many thanks,
Beth

Hi George, Thanks for your suggestions, they are very helpful and I'll give them a try. Just to clarify, a model using the proportional odds assumption would look like this (to use the example given): quietly runmlwin use4 cons (age lc1 lc2 lc3plus urban, contrast(1/3)), /// level2(district: (cons, ...