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From |
"Nick Cox" <n.j.cox@durham.ac.uk> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: RE: RE: How to tell with transformation is better? |

Date |
Thu, 28 Aug 2008 14:55:49 +0100 |

I think this misses the main point. On the whole, a response that is nearer normal in marginal distribution will be easier to model than one that isn't, but as is emphasised in every good regression text, the assumption that is being made in modelling is that of conditional normality given predictors and moreover that is probably the least important assumption you could make in any case. -qladder- does not address that. This point has been much laboured on the list! The main reason I can see for transformation here is that the relationship involving original and possibly transformed variables is more nearly linear than it was before. If you have just one x, the issue is best explored by a series of scatter plots. If you have several x, then commands like -mrunning- from the SJ can help get a handle on how successful the transformations have been. Whether you have one predictor or several, a basic criterion for a good model is that the residuals are essentially patternless. The standard postestimation graphs help here. Nick n.j.cox@durham.ac.uk Martin Weiss Well, if you want ideas for a whole range of transformations, try -qladder-. Other than that, you have provided the measure of a better transformation by employing the R-square. I do not think that there is a procedure in Stata that explicitly endorses such a model selection strategy. In terms of covariates, -stepwise- comes to mind... wangxin I have a linear regression model which is not very good since the R-square is very low.I test the Log-transformed dependent also, which turns to be not good also. I am wondering is there a way in Stata to test which transformation for variable is better? * * 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: How to tell with transformation is better?***From:*wangxin <seu_wangxin@yahoo.com.cn>

**st: RE: How to tell with transformation is better?***From:*"Martin Weiss" <martin.weiss@uni-tuebingen.de>

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