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From |
"FEIVESON, ALAN H. (AL) (JSC-SK) (NASA)" <alan.h.feiveson@nasa.gov> |

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

Subject |
st: RE: Comparison of a distribution with a value from the literature |

Date |
Fri, 18 Apr 2003 13:45:35 -0500 |

Andrea - Here's some thoughts on your question - perhaps they will be of some use. The only way to make use of the information that sd(A) = 0.2 is assume some distribution (such as a normal) for A. If you are willing to assume such a distribution, one easy approach you could try is to simulate many values of A (say 1000) and use -ranksum- to compare that distribution against your data. Of course, doing so would not give perfectly repeatable results except in the limit as the number of simulated A-values grows large. A theoretical approach to derive a repeatable result would be to do a binomial test for fixed A (see below), then average the conditional p-value over the assumed distribution of A. Whether this could be done analytically in closed form, depends on what distribution you use for A. You could approximate this second approach numerically by: (1) simulate a single value of A (2) do the fixed test below, then repeat (1) and (2) many times and look at the average p-value. The p-value from the -bitest- command is obtainable as the two-sided test p-vlaue, r(p). FIXED CASE: For the fixed A, nonparameteric case, suppose A0 is the hypothetical median from the literature and A is your data. Then just calculate the proportion of observations of A less than or equal to A0 and do a binomial test for the mean = 0.5. Or you could use the confidence interval command -ci- on a binary variable which is 1 if a <= A0, 0 otherwise and see if the confidence interval contains 0.5; e.g. scalar A0 = 1.0 gen na0 = A<= A0 bitest na0=0.5 ci na0 Al Feiveson -----Original Message----- From: Andrea Baccarelli [mailto:andreastata5@hotmail.com] Sent: Friday, April 18, 2003 12:43 PM To: statalist@hsphsun2.harvard.edu Subject: st: Comparison of a distribution with a value from the literature I have the following question: I am studying how the continuous variable A varies after a specific treatment. In addition to compare A after the treatment with A before the treatment or in controls (no treatment), I need to compare it also with standard reference values from the literature. Let's say that most book assume that A is equal to 1.0 with SD=0.2. I thought to use the ttest command: ttest A=1.0 I have two points: 1-This not take into account the variability (SD=0.2) of the measure taken from the literature. Does anyone have any suggestion about how to include it in the analysis? 2-Most variables in the study are not normally distributed. Is there any non-parametric test I can use to this end? [Stata's "ranksum" do not allow comparisons to a fixed value] Thanks, Andrea _________________________________________________________________ MSN 8 with e-mail virus protection service: 2 months FREE* http://join.msn.com/?page=features/virus * * 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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