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
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.
Jakob Ribbing, Ph.D.
Senior Consultant, Pharmetheus AB
Cell/Mobile: +46 (0)70 514 33 77
Phone, Office: +46 (0)18 513 328
Uppsala Science Park, Dag Hammarskjölds väg 52B
SE-752 37 Uppsala, Sweden
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