syntax necessary to constrain a random parameter to zero
Posted: Thu Jun 25, 2020 8:15 pm
Hi,
I am a very new user of R2MLwiN seeking to replicate an analysis model described in Blance et al. (2005, page 558)
https://journals.sagepub.com/doi/pdf/10 ... j92HfejdAw
(and attached).
The data consist of a single outcome variable (e.g. PPD) measured on two occasions (occ0 and occ1) in n patients.
The measurement occasion is dummy coded (e.g. -0.05 and +0.05).
The model comprises both random slopes and random intercepts.
The problem I have encountered is in specifying the model in such a manner that one of the four random parameters (i.e. σ2e0) is constrained to be zero.
Having corresponded with Dr. Blance I gather that the necessary constraint is straightforward to implement in MLwiN model code, and even easier for a single model when using the MLwiN user interface.
As in my application the model will be imbedded in an R script that processes a large number of data sets (on OSX and Linux platforms), MLwiN is not a viable option.
Using R2MLwiN I have been able to run basic random intercept and random slope models – for data with more than two levels of measurement occasion. In spite of combing through the documentation however, I am struggling to identify the appropriate R syntax to use in specifying this constraint (necessary when there are only two levels of occasion).
Any help would be much appreciated.
Richard
I am a very new user of R2MLwiN seeking to replicate an analysis model described in Blance et al. (2005, page 558)
https://journals.sagepub.com/doi/pdf/10 ... j92HfejdAw
(and attached).
The data consist of a single outcome variable (e.g. PPD) measured on two occasions (occ0 and occ1) in n patients.
The measurement occasion is dummy coded (e.g. -0.05 and +0.05).
The model comprises both random slopes and random intercepts.
The problem I have encountered is in specifying the model in such a manner that one of the four random parameters (i.e. σ2e0) is constrained to be zero.
Having corresponded with Dr. Blance I gather that the necessary constraint is straightforward to implement in MLwiN model code, and even easier for a single model when using the MLwiN user interface.
As in my application the model will be imbedded in an R script that processes a large number of data sets (on OSX and Linux platforms), MLwiN is not a viable option.
Using R2MLwiN I have been able to run basic random intercept and random slope models – for data with more than two levels of measurement occasion. In spite of combing through the documentation however, I am struggling to identify the appropriate R syntax to use in specifying this constraint (necessary when there are only two levels of occasion).
Any help would be much appreciated.
Richard