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

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

Subject |
st: RE: Non-paramtetric test for survey data |

Date |
Wed, 13 Apr 2005 17:50:34 +0100 |

Offlist someone commented to me >> Poisson is the ``right" command to use with a nonnegative dep var. >> Start with -whelp svypoisson- to which I replied >> I really would like to hear the case >> for regarding costs as a discrete >> variable. Let's suppose the data >> are like USD 123,456.78. How should >> that be treated? to which in turn the answer was >> Cents are certainly discrete, but the formulation of Poisson does not >> require discrete data, just E[y]=exp(Xb). See Wooldridge's Econometric >> Analysis of Cross Section and Panel Data Ch. 19 for details. I don't understand why the person concerned didn't want this contribution to be public. I certainly expect my arguments to be shot down if they are incorrect or misleading. Anyway, there the suggestion is. It seems to me that the spike at zeros still needs care. My guess is that the rest of the distribution doesn't start immediately at USD 0.01. Nick n.j.cox@durham.ac.uk -----Original Message----- From: Nick Cox [mailto:n.j.cox@durham.ac.uk] Sent: Wednesday, April 13, 2005 11:33 AM To: statalist@hsphsun2.harvard.edu Subject: st: RE: Non-paramtetric test for survey data This question was asked in slightly different form on Saturday. It got one reply, not answered here. It also seems to be based on various misconceptions, which may be why no one tried to answer the main question. The first is the idea that marginal normality is required for -svy- methods and that the alternative must be some non-parametric test. I don't know where you got that idea. Nor is it clear that the ideas behind -svy- can be combined usefully with non-parametric ideas. In your case, your interests in costs as the key response would not seem to march at all with degrading the data to ranks, and so forth. The second is that log transformation could ever be a satisfactory solution for data with a spike of zeros. Even with some fudge like log(response + 1) a spike will map to another spike. How problematic that is will depend upon circumstances, but transformation is of dubious relevance here. I don't know what you really need. It might be that you need to model those with non-zero costs and zero costs separately. I suspect that what you need involves a lot of programming from somebody. I doubt that it is canned anywhere. Nick n.j.cox@durham.ac.uk anju parthan > I am trying to compare if the total healthcare costs > are different in those who missed work and those who > did not miss work using lincom because I am using a > survey data. > > The total healthcare costs variable is not normally > distributed. A large proportion of individuals had > zero costs. I tried log transformation but it did not > change the distribution. So I guess I have to use > non-parametric tests. > > How can I use non-parametric tests with survey data? * * 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/

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