It's hard to see what your doing now, since the forum doesn't sort the responses. So no way to tell which reply goes with which post. In the future please just do one response. This isn't your fault - limitation of the forum.
Did you post your original distribution? Also, what is the variable, in laymans terms. Context can help with deciding what type of transformation to use, and there are certain standard transformation in diff industries.
Or you could check Box-Cox transformation . PROC TRANSREG or PROC MCMC can do that. Check example of them in documentation.
Interesting. I got this: data x; call streaminit(17); do i = 1 to 10000; FASTING_GLUCOSE = rand('lognormal'); x=rand('normal'); output; end; run; proc transreg data=x details pbo noprint; model boxcox(FASTING_GLUCOSE / convenient lambda=-2 to 2 by 0.01) = identity(x); output out=trans; run; proc univariate data=trans plots; histogram FASTING_GLUCOSE tFASTING_GLUCOSE ; run;
In layman terms I'm dealing with a contineous variable! Here is the distrubution before and after the log transformation!
@mantubiradar19 wrote:
In layman terms I'm dealing with a contineous variable! Here is the distrubution before and after the log transformation!
What type of continuous variable, blood pressure, stock price, number of asteroids heading towards earth?
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