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From |
"Newson, Roger B" <r.newson@imperial.ac.uk> |

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

Subject |
st: RE: interval ordinal |

Date |
Tue, 27 Nov 2007 14:50:11 -0000 |

By definition, you cannot "transform the format of data from an interval scale into an ordinal scale", because, interval data, by definition, are also ordinal. The categories "Nominal, Ordinal, Interval, Ratio" (abbreviated to NOIR) are nested categories. That is to say, all data are at least nominal, some nominal data are also ordinal, some ordinal data are also interval, and some interval data are also ratio. This is because nominal data are numbers (or vectors) X or Y for which it is meaningful to make the statements (in Stata notation) X==Y or X!=Y and ordinal data are numbers (or vectors) X and Y for which it is meaningful to make the statements X<Y, X>Y, X<=Y, or X>=Y and interval data are numbers for which it is meaningful to calculate X-Y or Y-X and ratio data are numbers for which it is meaningful to calculate X/Y or Y/X So, therefore ratio implies interval implies ordinal implies nominal, because positive numbers are a subset of numbers, which are a subset of sorted vectors, which are a subset of vectors which may or may not be sorted. Interval data can be analysed as interval data or as ordinal data. If we analyse them as interval data, then we are interested in estimating interval parameters, such as mean (or median) differences, with confidence limits or P-values. If we analyse them as ordinal data, then we are interested in estimating ordinal (or rank) parameters, with confidence intervals or P-values. Well-known rank parameters are Somers' D, Kendall's tau-a and Spearman's rho. Therefore, "analysing data as interval data" means estimating interval parameters, and "analysing data as ordinal data" means estimating ordinal (or rank) parameters. To get P-values for ordinal parameters, use -ranksum-, -ktau- or -spearman- in Stata. To get confidence intervals for ordinal parameters, use the -somersd- package, which you can download from SSC using the -ssc- command. More about ordinal parameters can be found on my website (see my signature below). I hope this helps. Best wishes Roger Roger Newson Lecturer in Medical Statistics Respiratory Epidemiology and Public Health Group National Heart and Lung Institute Imperial College London Royal Brompton campus Room 33, Emmanuel Kaye Building 1B Manresa Road London SW3 6LR UNITED KINGDOM Tel: +44 (0)20 7352 8121 ext 3381 Fax: +44 (0)20 7351 8322 Email: r.newson@imperial.ac.uk Web page: www.imperial.ac.uk/nhli/r.newson/ Departmental Web page: http://www1.imperial.ac.uk/medicine/about/divisions/nhli/respiration/pop genetics/reph/ Opinions expressed are those of the author, not of the institution. -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of H.Riese@med.umcg.nl Sent: 27 November 2007 13:19 To: statalist@hsphsun2.harvard.edu; statalist-digest@hsphsun2.harvard.edu Subject: st: interval ordinal Dear Statalist readers, I try to find the syntax to transform the format of data from an interval scale into an ordinal scale. Can someone help me? Thank you in advance for your reply, Harriette Riese * * 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/ * * 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/

**References**:**st: interval ordinal***From:*"H.Riese@med.umcg.nl" <H.Riese@med.umcg.nl>

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