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

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Standard normal Depvar |

Date |
Thu, 6 Aug 2009 12:37:13 -0400 |

Evans Jadotte<evans.jadotte@uab.es> : Your desideratum "How can I transform the Depvar in order to force xb^ to take on positive values?" and comments make no sense: N.B. exponentiation preserves rank. You can make x positive by su x replace x=x+2*abs(r(min)) for example, but then you can't take the square root and have it make sense. Maybe you want g y=sign(x)*sqrt(abs(x)) or somesuch? On Thu, Aug 6, 2009 at 12:26 PM, Evans Jadotte<evans.jadotte@uab.es> wrote: > Nick Cox wrote: >> >> Exponentiation will get you all positives. After that many options are >> open. >> >> Evans Jadotte wrote: >> >>> Nick Cox wrote: >>>> >>>> This produces zero or positive values. >>>> >>>> Less pedantically, if the variable is already standard normal, why does >>>> it need transforming? >>>> >>>> Nick >>>> >>>> Maarten buis wrote: >>>> >>>>> --- On Wed, 5/8/09, Evans Jadotte wrote: >>>>>> >>>>>> I am trying to run a regression where the dependent >>>>>> variable has a standard normal distribution (those of you >>>>>> familiar with the "wealth index based on the PCA analysis", >>>>>> this is my Depvar). However, I need to have the prediction to be all >>>>>> positive to use for transforming. >>>>>> How can I transform the Depvar in order to >>>>>> force xb^ to take on positive values? >>>>> >>>>> Here is one option: >>>>> >>>>> reg y x1 x2 >>>>> predict yhat >>>>> sum yhat, meanonly >>>>> gen yhatprime = yhat + abs(r(min)) >>>> >>>> * >>>> * 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/ >>> >>> Thanks to Maarten and Nick for their insight and comment on my question. >>> >>> I have both negative values and zeros in the /depvar /(/y/)/, /so/ /the >>> forecast, xb, will reflect such values. And as I will need sqrt(xb) for >>> further transformation at later stages, I need to transform /y/ so that xb >>> takes on all 'strictly' positive values and still preserve normality of /y/. >>> Maarten's suggestion indeed generates a 0 and the transformation I need is >>> in y (not yhat = xb). I have been trying a Box-Cox power transform but >>> results are not satisfactory. >>> >> >> * >> * 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/ > > Thanks Nick. However, exponentiation will result in a re-ranking of > individuals, which I must avoid. For instance, someone with a score -5 > compared with one whose score is 4, the former will end up being ranked > higher than the latter after exponentiating. I need to preserve the ranks > and normality after transforming. > > Thanks for the feedback, > > Evans > * > * 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/ > * * 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/

**Follow-Ups**:**Re: st: Standard normal Depvar***From:*Evans Jadotte <evans.jadotte@uab.es>

**References**:**Re: st: Standard normal Depvar***From:*Maarten buis <maartenbuis@yahoo.co.uk>

**Re: st: Standard normal Depvar***From:*Evans Jadotte <evans.jadotte@uab.es>

**Re: st: Standard normal Depvar***From:*Nick Cox <n.j.cox@stata.com>

**Re: st: Standard normal Depvar***From:*Evans Jadotte <evans.jadotte@uab.es>

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