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From |
catherine duggan <catherineduggan2002@yahoo.co.uk> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Fw: subgroups in cox regression |

Date |
Sun, 1 May 2011 18:36:57 +0100 (BST) |

Many thanks! ----- Original Message ---- From: Steven Samuels <sjsamuels@gmail.com> To: statalist@hsphsun2.harvard.edu Sent: Sun, 1 May, 2011 7:32:59 Subject: Re: st: Fw: subgroups in cox regression Sorry- ignore the snipped 'There is no "lik" at the end. Steve On May 1, 2011, at 10:19 AM, Steven Samuels wrote: Catherine: Effect modification means that the coefficient the exposure might differ between stages. To test it, you add an interaction or test for an interaction. One consequence of using the -if- statement is that it doesn't isolate a differential effect of your exposure variable, because all components of the model differ: 1) the baseline hazard; 2) the coefficient for race; and 3) the coefficient for your exposure. This is certainly a possible model and it is a good idea to check for proportionality of the baseline hazard by stage and race by using the strata() option in Stata. I'm also wondering whether you have checked that a linear term in your exposure variable is adequate; you can use the -fracpoly- command to find out. There is no "lik ****************************************** // If you have Stata Version < 11 (I presume so, since you use -xi- xi: stcox i.race i.stage*igf // Otherwise with Stata 11 stcox i.race c.igf##i.stage // add ", robust" to get robust standard error //The interaction term estimates the difference in igf slopes between the two stages. // You can get the slopes directly by: tab stage, gen(stage) // create indicators stage1 stage2 gen igf1= igf*stage1 gen igf2= igf*stage2 xi: stcox i.race stage1 igf1 stage2 igf2, nocons lincom igf1 - igf2 // estimate and test differences with Wald test **************************** Steve sjsamuels@gmail.com On Apr 30, 2011, at 10:40 PM, catherine duggan wrote: Hello I have what is probably a basic question, which is currently defeating me. I have run Cox regression with death as my outcome: my main exposure of interest is a a continuous variable (IGF) I have other covariates in the model - I will just refer to two of them, race (5 level) and tumor stage (2 level) Xi: stcox igf i.race i.stage I did the main analysis, and then did some exploratory subgroup analysis, with the usual caveats of smaller sample sizes and using a more conservative P value Eg Xi: stcox igf i.race if stage==1 However a reviewer gave the comment ' what you might want to do is to construct a model for effect modification - that is compare the model with no subgroup to one with trends fit for each subgroup - a 1 dgree of freedom likelihood ratio test - do see if the trends differ statistically - a test for homogeneity of trends. This would be more informative' Unfortunately I have no idea how to accomplish this - I wasn't sure whether this was a test for interaction or not. I'd appreciate any guidance Many thanks Catherine * * 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/

**References**:**Re: st: Fw: subgroups in cox regression***From:*Steven Samuels <sjsamuels@gmail.com>

**Re: st: Fw: subgroups in cox regression***From:*Steven Samuels <sjsamuels@gmail.com>

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