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From |
Austin Nichols <austinnichols@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: transformations for highly skewed dependent variable |

Date |
Wed, 9 Sep 2009 10:50:36 -0400 |

Well, sure, there are a lot of possible transformations e.g. arctangent or cube root, but what is the purpose of the transformation? Are you regressing y on X and thinking the errors won't be normal? In that case, you may not want to transform y. Also, have you considered that the y~=0 obs might be somehow qualitatively different? Note that the sd of return should be conditioned on size of investment, at least... clear all set seed 1 set obs 1000 g s=ceil(_n/250) g x=tan(_pi*uniform()*s-.5) tw kdensity x, name(x) g tx=atan(x) tw kdensity tx, name(atan) g cx=sign(x)*abs(x)^(1/3) tw kdensity cx, name(croot) g x2=(invnormal(uniform())*s)^3 tw kdensity x2, name(x2) g tx2=atan(x2) tw kdensity tx2, name(atan2) g cx2=sign(x2)*abs(x2)^(1/3) tw kdensity cx2, name(croot2) tw kdensity cx2, by(s) On Tue, Sep 8, 2009 at 4:27 PM, Dalhia<ggs_da@yahoo.com> wrote: > Dear Statalist, > > I have a dependent variable, Return on Assets, which is highly skewed - a high peak (I have lots of companies having ROA close to zero) and highly dispersed (I have about 200 values that are greater than 2.00 and lesser than -3.00). None of the usual corrections for skewed data (log, inverse, square) work because they pull in the values, hence increasing the peak. > > Is there some kind of data transformation available in stata that will make this data more normal? > > Thanks for your help. I appreciate it. > dalhia * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**References**:**st: transformations for highly skewed dependent variable***From:*Dalhia <ggs_da@yahoo.com>

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