Using weights in multivariate multilevel models
Posted: Thu May 10, 2018 12:36 pm
Hi all,
I am trying to run two multivariate multilevel models, one with Propensity score weights (standardized inverse probability of treatment weights; SIPTWs) and the other without weights.
My data consists of two dependent variables, lnPRI_E (the continuous one) and PRI_E (the binary one).
I have merged (replicated) the weight variable SIPTW_1 to a long format within MLwiN using the Data Manipulation tool.
The problem here is that whenever I try to apply weights in the multivariate multilevel model, it shows an error sign indicating that "Input lists must have Gamma block components."
(When I set two continuous variables, the same message appears, but sometimes MLwiN shows results that are exactly the same as those without weights.)
Would there be anything that I'm missing or would it be impossible to run weighted multivariate multilevel models in MLwiN?
Many thanks in advance.
I am trying to run two multivariate multilevel models, one with Propensity score weights (standardized inverse probability of treatment weights; SIPTWs) and the other without weights.
My data consists of two dependent variables, lnPRI_E (the continuous one) and PRI_E (the binary one).
I have merged (replicated) the weight variable SIPTW_1 to a long format within MLwiN using the Data Manipulation tool.
The problem here is that whenever I try to apply weights in the multivariate multilevel model, it shows an error sign indicating that "Input lists must have Gamma block components."
(When I set two continuous variables, the same message appears, but sometimes MLwiN shows results that are exactly the same as those without weights.)
Would there be anything that I'm missing or would it be impossible to run weighted multivariate multilevel models in MLwiN?
Many thanks in advance.