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From |
"Polis, Chelsea B." <cpolis@jhsph.edu> |

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

Subject |
st: RE: RE: Choosing control variables in survival analysis |

Date |
Mon, 15 Jun 2009 17:11:20 -0400 |

Many thanks for your response, Kieran! I am indeed interested in the effect of a specific variable on time to death. I tried to use epiconf, but think that it might not be possible for survival data with multiple records with gaps, since a singular "time" variable is required. Am I missing something? Cheers, Chelsea -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Kieran McCaul Sent: Wednesday, June 10, 2009 5:12 PM To: statalist@hsphsun2.harvard.edu Subject: st: RE: Choosing control variables in survival analysis Hi Chelsea, The strategy will differ depending on what the purpose of the survival analysis is. Broadly speaking, there are two different reasons for modelling data: (1) You are interested in the effect of a particular variable and you want to estimate this by accounting for the possible confounding effects of other variables, or (2) you are interested in finding a parsimonious set of predictor variables. In (1), statistical significance plays no role in selecting confounders. Confounding is a bias. A variable either confounds your exposure the estimate or it doesn't. In (2), the fit of the model is important, so the significance of the variables you choose will important. It sounds like you have an exposure that you're interested in, so I would suggest that you select variables based on their confounding effect. The strategy is called the "change-in-estimate" method. Have a look at: Greenland S (1989). Modeling and variable selection in epidemiologic analysis. Am J Public Health 79(3): 340-9. This outlines the strategy and Zhiqiang Wang wrote an ado file -epiconf-, which you may find useful. Also, a chi-square test of exposure against outcome will generally be of no use because it does not account for time to event. ______________________________________________ Kieran McCaul MPH PhD WA Centre for Health & Ageing (M573) University of Western Australia Level 6, Ainslie House 48 Murray St Perth 6000 Phone: (08) 9224-2701 Fax: (08) 9224 8009 email: Kieran.McCaul@uwa.edu.au http://myprofile.cos.com/mccaul http://www.researcherid.com/rid/B-8751-2008 ______________________________________________ Man is a credulous animal, and must believe something; in the absence of good grounds for belief, he will be satisfied with bad ones. Bertrand Russell -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Polis, Chelsea B. Sent: Thursday, 11 June 2009 2:04 AM To: statalist@hsphsun2.harvard.edu Subject: st: Choosing control variables in survival analysis Dear Statalisters, I am doing a survival analysis, which uses multiple records per individual to incorporate time-varying exposure information. I plan on building two multivariate Cox regression models: (Model A) includes potential confounders based strictly on statistical significance, and (Model B) includes those variables plus others I think should be included based on theoretical concerns or comparability to previous studies. I have been including a variable in Model A if a variable is associated with my dichotomous exposure (in chi2 tests) and time to event (in univariate Cox regression). However, I am not sure whether to include it in Model A if it is NOT significantly associated with time to event in Cox regression, but IS significantly associated with having HAD the event in a chi2 test? Your thoughts would be much appreciated. * * 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/ * * 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**:**st: RE: RE: RE: Choosing control variables in survival analysis***From:*"Kieran McCaul" <Kieran.McCaul@uwa.edu.au>

**References**:**st: Choosing control variables in survival analysis***From:*"Polis, Chelsea B." <cpolis@jhsph.edu>

**st: RE: Choosing control variables in survival analysis***From:*"Kieran McCaul" <Kieran.McCaul@uwa.edu.au>

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