Hi Tingjie,

Assuming (zero and) negative parameter values are not allowed,  you could 
change from e.g. a linear model to a power model, which is as close as possible 
to the linear model, in the range of covariate values from the original 
publication.

If the publication lists e.g. median, mean and 95% CI of the covariate values 
(maybe this is hoping for too much?),  then you can generate e.g. a normal or 
log-normal distribution of covariate values that reflect these statistics as 
closely as possible.
Then you can optimize the power model to resemble the linear model as closely 
as possible on these covariate-parameter data.

Best wishes

Jakob




Jakob Ribbing, Ph.D.

Senior Consultant, Pharmetheus AB



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