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ex: x=2 and y=3 find sum with only one parameter.

]]>ex: x=2 and y=3 find sum with only one parameter.

]]>I have an application question not sure whether your guys know the sure answer:

How to obtain the adjusted differences with 95% confidence intervals in original scale for the dependent variables that need to be log-transformed before you do the GLM for a dichotomous predictor variable? We often need to use the GLM model to account for variations of multiple co-variables

(categorical or continuous))? If the data are in original scale, this is very simple as these are the regression coefficients and 95% CIs from GLM. However, sometimes, the dependent variable is highly skewed, and violate the assumption of Normality, therefore, data log-transformation is needed before you do the GLM. In such cases, the regression coefficients you obtained are effectively the ratio of the two adjusted means in the original scale, so you can not obtain the confidence limits of the adjusted difference directly.