Basically I have a positively skewed distribution and want to make a

transformation so it is normally distributed. Usually I would just

make a logarithmic transformation and this would be fine. However in

this instance some of the distribution I want to transform is

negative, and obviously I can't take the log of a negative value.

What I have tried so far is just adding a random constant to each

observation to force the distribution to be positive (I.e. shift it to

the right) and then make a logarithmic transformation. However im not

particularly happy doing this as when I come to use this as the

dependant variable in subsequent regression analysis I believe the

results will vary with my choice of the random constant I added to

force the distribution positive.

Does anyone know if the way i have approached this problem is just, or

have any further suggestions for what i could do?