The conventional models used for dose-response meta-analyses only consider the variation for the response variable. I am trying to find a model for dose-response meta-analysis (both the dose and the response variables are continuous) which also takes the variation (SD) in the dose (exposure) variable and possible confounding variables (for adjustment in the model) into account. I will be thankful if you also guide me about the statistical package that I should use for such an analysis.
Hi!
Up to now I´m not aware of such model (but I might be not updated). A dose-response gradient can be observed in subgroup meta-analyses, in which an explanatory variable (mean dose, used to create subgroups) is associated with the outcome (mean difference of response).
Also, you can perform a meta-regression if you have enough studies included in your meta-analysis. Meta-regressions are similar in essence to simple regressions, in which an outcome variable is predicted according to the values of one or more explanatory variables. In meta-regression, the outcome variable is the effect estimate (mean difference of response) and the explanatory variable is a characteristic of the studies that might influence the size of intervention effect (mean dose).
I hope this helps.
Good luck!
Thank you Erika. In fact meta-regression tests the linear association. and does not consider a variation for the independent variable. Like the current non-linear dose-response analyses.
In this question I want to find a model which considers the variation in the dose and also the response variables.
Dear Amin,
Please check dosresmeta package for R developed by Alessio Crippa. It currently allows running a dose-response model with continuous outcomes (Mean difference or SMD). Here's the link to the package:
https://cran.r-project.org/web/packages/dosresmeta/dosresmeta.pdf
Best,
Jakub
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