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From |
"Martin Weiss" <martin.weiss1@gmx.de> |

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

Subject |
st: AW: Bootstrap and p-values |

Date |
Sat, 19 Sep 2009 18:55:41 +0200 |

<> " Also it is not clear to me if the reported bias is a quantity that adds to the standard error or must be subtracted from the standard error in calculating the variance." Not sure what you mean. The bias is the difference btw the coefficient estimate of your chosen estimator and the mean of the bootstrap estimates. The standard error is the standard deviation of those bootstrap estimates, as seen in this code: ************* sysuse auto, clear //get bs estimates bs, reps(200) saving(myfile, /* */ replace) seed(1020): /* */ reg pr we le he //store coeffs in -local-s foreach var of varlist weight length headroom{ loc `var'coeff=_b[`var'] } //get saved file of bs estimates u myfile, clear //calculate bias and bs standard error foreach var in weight length headroom{ qui su _b_`var' di in red "Coeff `var', Bias (Mean of Bootstraps-Original): " /* */ r(mean)-``var'coeff' _n /* */ "Bootstrap se: " r(sd) _n } //compare to official results estat boot, all ************* HTH Martin -----Ursprüngliche Nachricht----- Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Giulio Rizzoli Gesendet: Samstag, 19. September 2009 17:17 An: statalist@hsphsun2.harvard.edu Betreff: st: Bootstrap and p-values This mail didn't go through twice I try the third time after reading the FAQ instructions. Dear all: Many medical variables are correlated, so I'm using the bootstrap program to verify the most frequently extracted variables within a backward and forward algorithm. In the example below Nyha4 is by far the most extracted variable and therefore the most significant statistically. I usually publish tables of the selected variables with their confidence limits. I imagine that the bias corrected confidence limits provided by bootstrap are the most correct ones. Nonetheless until now I have always published the normal confidence limits, because the p-value can be easily controlled from reviewers, using the formula to calculate the variance under the normality assumption: (lnucl-lnlcl)/(2*1.96))^2 . // lnucl=log of upper C. L. lnlcl=log of lower C. L. I would like to know there is a method to calculate the p_value starting from the BC confidence limits. Also it is not clear to me if the reported bias is a quantity that adds to the standard error or must be subtracted from the standard error in calculating the variance. The BC confidence limits are narrower. So i imagine that bias should be subtracted from standard error because bias relates to the part of measurement error that is casual. Am I correct? If it is so it is important to have a p-value for this estimate but the calculation with the usual zeta= _b/_se assumes a normality distribution. Is it valid in this setting ? It woul'd be wonderful if someone has a routine to calculate the different p-values starting from the ereturn list of the bootstrap saved values or could show how to calculate BC related p-values. . bootstrap "sw, pr(.1) pe(.05): stcox fsex AOI sonoreint age nyha4 CPRENF CPRESPF CPIABP" _b,reps(1000) dots command: sw , pr(.1) pe(.05) : stcox fsex AOI sonoreint age nyha4 CPRENF CPRESPF CPIABP statistics: b_sesso = _b[fsex] b_age = _b[age] b_nyha4 = _b[nyha4] ............................................................................ .... >.... Bootstrap statistics Number of obs = 327 Replications = 1000 ---------------------------------------------------------------------------- -- Variable | Reps Observed Bias Std. Err. [95% Conf. Interval] -------------+-------------------------------------------------------------- -- b_fsex | 597 -.3829885 -.1357204 .138327 -.6546561 -.1113208 (N) | -.8652664 -.3303381 (P) | -.4775621 -.2981049 (BC) | -1.328869 .6971875 (BC) b_age | 550 .0824691 .0245982 .0309384 .021697 .1432412 (N) | .0681392 .1776492 (P) | -.1053623 .1156664 (BC) b_nyha4 | 845 1.043275 .2214171 .3910648 .2757012 1.810849 (N) | .652275 2.103901 (P) | .5398257 1.679764 (BC) ---------------------------------------------------------------------------- -- Note: N = normal P = percentile BC = bias-corrected * * 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/ * * 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/

**Follow-Ups**:**Re: st: AW: Bootstrap and p-values***From:*Giulio Rizzoli <giulio.rizzoli@unipd.it>

**References**:**st: Bootstrap and p-values***From:*Giulio Rizzoli <giulio.rizzoli@unipd.it>

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