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From |
"Martin Weiss" <martin.weiss1@gmx.de> |

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

Subject |
RE: st: Create a normalized variable |

Date |
Thu, 20 Nov 2008 16:31:42 +0100 |

Line for the server... "Sometimes, the term is used for standardization. A common method is to subtract the mean and divide by the standard deviation (the results are sometimes called z-scores). Again you cannot mean that as the resulting variable will not range between 0 and 1." Note that this would be most easily achieved via -egen, std()- HTH Martin -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Maarten buis Sent: Thursday, November 20, 2008 4:26 PM To: statalist@hsphsun2.harvard.edu Subject: Re: st: Create a normalized variable --- mmolina@uniroma3.it wrote: > I need to create a normalized variable between 0 and 1 starting from > another variable of 1063 observations with ranks between 0 and 8 This very much depends on what you mean with normalized. Sometimes it means a transformation that will result in a variable that is nearer to a normal (Gaussian) distribution. You cannot mean that, as than the resulting variable cannot range between 0 and 1 (as a normal distribution ranges between minus infinity and plus infinity). Sometimes, the term is used for standardization. A common method is to subtract the mean and divide by the standard deviation (the results are sometimes called z-scores). Again you cannot mean that as the resulting variable will not range between 0 and 1. An alternative way to standardize would be to use percentile ranks, which gives for each respondent the proportion of respondents thas smaller, poorer, dumber, etc than that respondent. This will give you a standardized variable wich ranges between 0 and 1. The downside of this approach is that it is less common so you have more to explain, and that it is a non-linear transformation, in particular you only keep information obout the ordering of individuals and loose information about the distances between them. Don't get me wrong though, I like this form of standardization, it is just not suitable for every application (which should not be a big surprise). The way to compute these is discussed here: http://www.stata.com/support/faqs/stat/pcrank.html Finaly, a linear transformation that will lead to a score between 0 and 1 is to simply divide that variable by 8. Hope this helps, Maarten ----------------------------------------- Maarten L. Buis Department of Social Research Methodology Vrije Universiteit Amsterdam Boelelaan 1081 1081 HV Amsterdam The Netherlands visiting address: Buitenveldertselaan 3 (Metropolitan), room N515 +31 20 5986715 http://home.fsw.vu.nl/m.buis/ ----------------------------------------- * * 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/

**References**:**st: Create a normalized variable***From:*mmolina@uniroma3.it

**Re: st: Create a normalized variable***From:*Maarten buis <maartenbuis@yahoo.co.uk>

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