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From |
Vasan Kandaswamy <vasan.kandaswamy@ki.se> |

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

Subject |
RE: st: Quantile regression |

Date |
Wed, 19 Sep 2012 21:33:33 +0000 |

Many thanks Nick. Now, I have given up on ANOVA since I cannot derive p values for gender seperately, but did a regression. A quantile regression this way comes up this way bysort bmi_q sex:sum g0mmol bysort sex: qreg bmi fast_glucose age pr ( adjusted for age) I tabulate the output this way BMI Q1 Q2 Q3 Q4 Beta (95%CI) P value Male 5.3 5.4 5.5 5.6 2.61 (1.46, 3.76) 8.91 x 10^-06 Female 5.4 5.4 5.4 5.7 0.36 (-0.15, 0.86) 0.168 IF you actually look at the mean glucose values in Q1-Q5, there is not much difference, but the regression shows a clear difference with p values of males significant, while females are not. Could you please explain of my approach is correct. The basic question I would like to ask is if the fold change from Q1 to Q5 is significant. Best regards, Vasan ________________________________________ From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of Nick Cox [njcoxstata@gmail.com] Sent: Wednesday, September 19, 2012 9:15 PM To: statalist@hsphsun2.harvard.edu Subject: Re: st: derive exact p values from ANOVA models 1. For every -anova-, there is an equivalent -anova, regress-. 2. 2*normal(-abs(beta/se)) is not "exact" for regression; it is a rule of thumb even if all assumptions are satisfied, as t statistics are involved. 3. See Maarten Buis' Tip: full reference and .pdf at http://www.stata-journal.com/article.html?article=st0137 On Wed, Sep 19, 2012 at 8:03 PM, Vasan Kandaswamy <vasan.kandaswamy@ki.se> wrote: > Dear Jay, > > Thank you very much. I have now used the two way anova for comparison. Since the groups are equal sizes, regression model is not thought of at the moment. > > I have another quick question, is there a way that I could obtain the exact p values from anova. > I do not want to show p=<0.0001 for all variables, but would like to be more specific. > While I do regression models, I use beta and SE to derive exact p values this way - > di (2*normal(-abs(beta/se))). but this is not possible with ANOVA. > > Could someone suggest how to get exact p values from ANOVA ? > Many thanks ! > > Vasan, > PhD student, > Karolinksa Institutet, Stockholm, Sweden > > > ________________________________________ > From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] on behalf of JVerkuilen (Gmail) [jvverkuilen@gmail.com] > Sent: Wednesday, September 19, 2012 1:01 AM > To: statalist@hsphsun2.harvard.edu > Subject: Re: st: ANOVA for quartiles > > On Tue, Sep 18, 2012 at 6:08 PM, Vasan Kandaswamy <vasan.kandaswamy@ki.se>wrote: > >> Dear Statalisters, >> >> I intend to perform an ANOVA to compare the means of a variables across >> quartiles of BMI ( body mass index) in two genders (male and female ). > > Why not a two-way model? > > anova myoutcomevar gender##bmi_quartiles > > Or the equivalent sequence of regression models if the groups are not > of equal size. > * * 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: Quantile regression***From:*David Hoaglin <dchoaglin@gmail.com>

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