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From |
"Wallace, John" <John_Wallace@affymetrix.com> |

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

Subject |
st: RE: RE: Regression across variables |

Date |
Tue, 11 Nov 2003 11:02:23 -0800 |

Thanks Nick - any implication of non-orthodoxy is purely my ignorance in these matters. My formal stat background is pretty weak. What I was trying to show is that there is in effect a variable orthogonal to the matrix of observations (the Molarity value) that I would like to regress the row of values for each observation against the row of Molarity values (rather than the column of A values against the column of B values, for example). The question would be how to introduce the molarity values into the dataset (each variable corresponds to a concentration level that is being tested) and how to tell stata to use it in the regression. If the answer is the same, I'll just have to plug away and see if I can figure out how my mental picture fits into what you said. I appreciate the help! -JW -----Original Message----- From: Nick Cox [mailto:n.j.cox@durham.ac.uk] Sent: Tuesday, November 11, 2003 9:59 AM To: statalist@hsphsun2.harvard.edu Subject: st: RE: Regression across variables As I understand it, this is more orthodox than you imply, and you could think of the analysis as a series of regressions, except that you have no covariates, at least that you're showing us. That's not fatal, however. . regress A says in effect estimate the mean of A, and much of the output you get is based on the assumption that A follows, or should follow, a normal (Gaussian, central) distribution. Following that with . test _cons = 0.5 is, perhaps, a long-winded way of going . ttest A = 0.5 except that if you do have covariates, the -regress- framework is the one on which you can build. Ronan Conroy's paper in SJ 2(3) 2002 is a very nice example of this principle. Having said that, the assumption of normality is important. It wouldn't surprise me if the distributions were skewed and (say) gamma-like, so that -glm- is then a better framework. Nick n.j.cox@durham.ac.uk Wallace, John > > Hi Statalisters. I'm trying to get Stata to perform a > regression in a data > structure different from the usual yvar xvar arrangement. > I'll diagram the > data set to show what I mean: > > Molarity 0.5 1 2 3 > > Variable A B C D > Observ1 .22 .45 .99 1.4 > Observ2 .23 .5 .98 1.5 > Observ3 .19 .38 1.1 1.42 > > Molarity in this case would be the constant associated with > each variable. > The observations are measurements of the system attempting > to quantify the > molarity. The idea would be to generate additional > variables that contain > the various regression results of the observations vs Molarity. > > My data set at this point is just variable name against > observation number. > I don't know how to associate each variable with the > corresponding molarity, > or how to tell Stata to perform a regression in this way. > Do I have to > -reshape- or is there another way? * * 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/

**Follow-Ups**:**st: RE: RE: RE: Regression across variables***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

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