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From |
"Dedman, Dan" <D.Dedman@ljmu.ac.uk> |

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

Subject |
st: Quantile question |

Date |
Fri, 29 Feb 2008 15:40:35 -0000 |

We want to agree on a method for producing quantiles so we are all working to the same algorithm. I was intrigued by the way Stata does it and wondered where this came from and what the justification is. If we have 150 observations to be grouped into quintiles - this is easy. But what if we had 151, or 152, 153 or 154 observations? This is how Stata 9 does it using -xtile- : xtile newvar=rank, nquantiles(5) ---------------------------- q1 31 31 31 31 q2 30 30 31 31 q3 30 31 30 31 q4 30 30 31 31 q5 30 30 30 30 ---------------------------- All 151 152 153 154 and using the -cut- function from -egen- : egen q2=cut(rank), group(5) ---------------------------- q0 30 30 30 30 q1 30 30 31 31 q2 30 31 30 31 q3 30 30 31 31 q4 31 31 31 31 ---------------------------- All 151 152 153 154 So the two methods work in opposite directions, but are otherwise consistent in where they place the 'extra' 1 to 4 observations. I am quite to adopt the Stata approach, but some of my colleagues do not use Stata, so I would like to describe how the Stata algorithm works, and why Stata does it this this way as opposed to any other way. Is this a general convention, or more easy to justify statistically or otherwise, or just a case of find a way that works and stick with it. Many thanks Daniel Dedman Public Health Information Analyst/Project Manager North West Public Health Observatory * * For searches and help try: * http://www.stata.com/support/faqs/res/findit.html * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

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