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Hi @dmphillippo. According to Dias 20181 (page 239-240), in a meta-regression model with a common interaction "there is a single interaction term b that applies to relative effects of all the treatments relative to treatment 1". However, when trying to fit such a model, multinma requires treatment classes to be specified in the network.
Would you accept a PR that allows class_interactions = "common" without specified treatment classes in the network? nma() would then simply assume there are two classes: one for the reference treatment, and one for all others. Maybe this should only work if the user explicitly set a trt_ref in the network and/or with a regression formula without an interaction with the treatment (class), i.e. ~ stroke.
Footnotes
Dias, S., Ades, A. E., Welton, N. J., Jansen, J. P., & Sutton, A. J. (2018). Network meta-analysis for decision-making. John Wiley & Sons. ↩
The text was updated successfully, but these errors were encountered:
Hi @ndunnewind, sorry for the very slow response - I've been away from work for much of the last couple of years.
My intention with forcing the user to specify trt_class even to fit the single common interaction model was that this model makes some fairly strong assumptions, and requiring trt_class makes the user explicitly specify them.
I can see that this is a bit fiddly from a user perspective, however.
Perhaps we should allow the user to specify class_interactions = "common" without classes in the network, and give a warning like: warn("Using a single common interaction parameter for all treatments against the reference treatment. Specify treatment classes in the network to change this. See set_*() argument `trt_class`.")
This could maybe be demoted to a note with inform() if the user has explicitly set trt_ref.
What do you think? Happy to review a PR (if you're still interested 2 years later!)
Hi @dmphillippo. According to Dias 20181 (page 239-240), in a meta-regression model with a common interaction "there is a single interaction term b that applies to relative effects of all the treatments relative to treatment 1". However, when trying to fit such a model, multinma requires treatment classes to be specified in the network.
A solution would be to manually define the treatment classes "placebo" and "treatment".
Would you accept a PR that allows
class_interactions = "common"
without specified treatment classes in the network?nma()
would then simply assume there are two classes: one for the reference treatment, and one for all others. Maybe this should only work if the user explicitly set atrt_ref
in the network and/or with a regression formula without an interaction with the treatment (class), i.e.~ stroke
.Footnotes
Dias, S., Ades, A. E., Welton, N. J., Jansen, J. P., & Sutton, A. J. (2018). Network meta-analysis for decision-making. John Wiley & Sons. ↩
The text was updated successfully, but these errors were encountered: