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From |
"Hugh Robinson" <hugh.robinson@umontana.edu> |

To |
"Joseph Coveney" <jcoveney@bigplanet.com>, "Statalist" <statalist@hsphsun2.harvard.edu> |

Subject |
RE: st: Cox Model Collinearity |

Date |
Thu, 31 Jul 2008 20:26:48 -0600 |

Thanks Joseph, Yes the problem exists in most of my models. The groupings are time-varying as the geographic areas were adjacent, and animals were free to come and go as they pleased. I'm wondering if a solution would be to treat each group as a strata? Thus each group would have its own baseline hazard function. HR -----Original Message----- From: Joseph Coveney [mailto:jcoveney@bigplanet.com] Sent: Thursday, July 31, 2008 6:24 PM To: Statalist Cc: Hugh Robinson Subject: Re: st: Cox Model Collinearity Hugh Robinson wrote: I am trying to model wildlife survival data (multiple encounter records for 117 individual cougars over 9 years). I have divided the data into several "groupings" based on varying hunting pressure and geographic location. I wish to use Cox modeling and post estimation AIC (estat ic) to test which grouping best fits the mortality patterns observed. For instance, all areas were hunted heavily for the first 3 years (group 1) at which point one area was protected (group 2) while hunting continued in the remainder of the study area (group 3). A second model would test if dividing the study animals into 6 groups (i.e. 2 geographic areas, 3 time periods) provides a better fit. Each group is coded as a string variable. The outputs I receive from STATA suggest that several groups are collinear resulting in no values of Standard Error and erroneous hazard ratios. For instance, in the above model group 3 and group 1 are collinear. With group 1 coded as the dummy variable, STATA provides a hazard ratio of 0.99 and no standard error, z, or p-value. I'm not sure if I can trust the AIC values I receive from post estimation. Can anyone suggest how I should approach this collinearity issue? ------------------------------------------------------------------------ -------- Grouping two geographic areas together at Time 1 as Group 1, and then separately at Time 2 as Groups 2 and 3 wouldn't give rise to collinearity by itself. If the problem is caused by following cougars in the same geographic area through both times, then you would be seeing the same problem in the second model. I take it that you are seeing the problem with both models--is that correct? If so, have you looked into what Stata has for time-varying covariates (predictors) in Cox proportional-hazard models? I'm not sure how helpful it will be in your circumstances, but if you haven't already seen what's available, then type findit cox time varying in Stata's command window and follow the hyperlinks. The commands there might allow for a better parameterization of your model. Joseph Coveney * * 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/

**References**:**Re: st: Cox Model Collinearity***From:*"Joseph Coveney" <jcoveney@bigplanet.com>

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