[Date Prev][Date Next][Thread Prev][Thread Next][Date Index][Thread Index]

From |
Glenn Goldsmith <glenn.goldsmith@gmail.com> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
st: Pairwise correlation of non-continuous variables |

Date |
Thu, 10 Sep 2009 15:01:46 +0100 |

<> I'm not an expert on this, but seeing as no-one else has replied, here's my 2 cents: 1. Kendall's tau seems a reasonable test for this situation. However, you probably want to use the -stats(taub)- option rather than the default -stats(taua)- if you have tied values, as this will deal with them better. 2. The -p(0.05)- option is short for -print(0.05)- and only displays correlations that are significant at the specified level. If you want to display all the coefficients, you could instead use -star(0.05)-, to indicate which are significant. 3. Given that you're testing multiple correlations, you may also want to think about correcting the significance levels for this to control the overall error rate using the -bonferroni- or -sidak- options. HTH, Glenn "Sockolow, Paulina" <psockolo@jhsph.edu> wrote: Hi Stata list, I have data from a small survey , and wanted to test for pairwise correlation among the items. There are less than 40 subjects, and 21 ordinal variables. I wanted to use a non-parametric test, setting statistical significance at 0.05, and ran: ktau <variable list> , pw p(0.05) 1. Was this the correct test for my question? 2. The output does not look like pairwise correlation output in that only some pairs have a value reported. Because of the ktau command, and the values reported are between 0 and 1, I am guessing the values are Kendall's tau. How do I interpret the output? Did Stata return only pairs that are correlated? Thank you, Paulina * * 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/

- Prev by Date:
**Re: st: Marginal effect for Probit model** - Next by Date:
**st: RE: Creating interaction terms of 30 continuous variables** - Previous by thread:
**st: Pairwise correlation of non-continuous variables** - Next by thread:
**st: Re: spliting multiple response variable** - Index(es):

© Copyright 1996–2022 StataCorp LLC | Terms of use | Privacy | Contact us | What's new | Site index |