Gaussian model GLM summary(model)$dispersion

Hi,  

I have some data that is log-normally distributed and I am using a glm, type
Gaussian to fit the logs.

I would like to know the expected values within the context of the lognormal
model. 

I am unsure whether I have to use:

Expected_values= exp(fitted(model)+sqrt(summary(model)$dispersion)/2)

OR 

Expected_values= exp(fitted(model)+summary(model)$dispersion)/2)


Your help is much appreciated.  



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