tag:blogger.com,1999:blog-1275149608391671670.post5773998631726310062..comments2023-09-28T06:13:40.704-04:00Comments on SAS and R: Example 7.42: Testing the proportionality assumptionKen Kleinmanhttp://www.blogger.com/profile/09525118721291529157noreply@blogger.comBlogger14125tag:blogger.com,1999:blog-1275149608391671670.post-9038513719795636012017-03-23T08:19:24.781-04:002017-03-23T08:19:24.781-04:00Hi,
Thanks for this post, but what would you do ...Hi, <br /><br />Thanks for this post, but what would you do if you have age as the time scale? I have data set up as a single individual per row with the model statment written as: <br />(age_in, age_out)*no_deaths (0)=drug_type<br /><br />How do you assess proportional hazards in this case? I can't put in (age_out-age_in) as the x in the sgplot command... <br /><br />Thanks!<br /><br />March 23, 2017Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-1275149608391671670.post-27173556732360626252017-03-23T08:18:21.824-04:002017-03-23T08:18:21.824-04:00This comment has been removed by the author.Anonymoushttps://www.blogger.com/profile/18393628322054247472noreply@blogger.comtag:blogger.com,1999:blog-1275149608391671670.post-21144966475262055602015-03-21T17:41:43.304-04:002015-03-21T17:41:43.304-04:00Hello! This is so helpful! So I know that my data ...Hello! This is so helpful! So I know that my data fails the proportionality assumption, and it fails around day 90 when the survival curves cross on a Kaplan-Meier graph. I want to fit 2 models, one early and one late-- but how do I censor the time intervals without excluding patients? Awahttps://www.blogger.com/profile/17399303584455804511noreply@blogger.comtag:blogger.com,1999:blog-1275149608391671670.post-82611073326077818242014-07-13T14:07:12.546-04:002014-07-13T14:07:12.546-04:00Does anyone know how to create a heaviside functio...Does anyone know how to create a heaviside function in SAS when the predictor variable has 3 categories?Anonymoushttps://www.blogger.com/profile/10778331267390532406noreply@blogger.comtag:blogger.com,1999:blog-1275149608391671670.post-32981699569335054012014-04-27T15:44:52.518-04:002014-04-27T15:44:52.518-04:00Thanks Ken for your reply! I am looking at antidep...Thanks Ken for your reply! I am looking at antidepressant use and risk of dementia in a propensity score matched sample. There are 732 patients in each group (Parox and other).<br /><br />The percentage of censoring is 92.3% (677/732) in Parox group and 92.4% (676/732) in other group. This is a propensity score matched sample. I only controlled for osteoporosis in the adjusted analysis as it was significant even after matching. I only tested for Schoenfeld residuals using supermum test using 1000 replications(p=0.0650). I checked for KM curves using log rank test (p=0.635). <br /><br />I also feel that it is a sample size issue as 55/732 had dementia in the Parox group and 56/732 got dementia in the other group in the matched sample.<br />Anonymoushttps://www.blogger.com/profile/10778331267390532406noreply@blogger.comtag:blogger.com,1999:blog-1275149608391671670.post-26354451655311510572014-04-27T15:35:34.644-04:002014-04-27T15:35:34.644-04:00This comment has been removed by the author.Anonymoushttps://www.blogger.com/profile/10778331267390532406noreply@blogger.comtag:blogger.com,1999:blog-1275149608391671670.post-81265429348882242502014-04-23T10:28:39.783-04:002014-04-23T10:28:39.783-04:00Without seeing the data, my guess would be a lack ...Without seeing the data, my guess would be a lack of power. If the sample size (or number of events) is small, I'd be pretty concerned about the proportionality assumption.Ken Kleinmanhttps://www.blogger.com/profile/09525118721291529157noreply@blogger.comtag:blogger.com,1999:blog-1275149608391671670.post-18266195273730112612014-04-20T15:08:38.080-04:002014-04-20T15:08:38.080-04:00Thanks for the post. It is really helpful. I perfo...Thanks for the post. It is really helpful. I performed survival analysis and KM curve cross each other suggesting that PH assumption is not met but my schenfeld test is not significant. So, could you please tell me what can be the reason that Schoenfeld test is not significant even though KM curves are crossing?Anonymoushttps://www.blogger.com/profile/10778331267390532406noreply@blogger.comtag:blogger.com,1999:blog-1275149608391671670.post-623558719511165192013-09-18T14:24:23.986-04:002013-09-18T14:24:23.986-04:00The thing about that interaction is that (IIUC) it...The thing about that interaction is that (IIUC) it needs to be calculated at every censoring time and every failure time in the data set. The SAS code calculates the interactions within the PHREG procedure to do this. If you just calculate a static one-time variable, you'll get a different and wrong answer.<br /><br />I'm 100% sure it's possible to do this analysis in R-- it's just that for the purposes of assessing proportionality, the approach we show here is easier to implement.Ken Kleinmanhttps://www.blogger.com/profile/09525118721291529157noreply@blogger.comtag:blogger.com,1999:blog-1275149608391671670.post-70327008606247589422013-09-18T09:31:30.795-04:002013-09-18T09:31:30.795-04:00I don't think that "In R the time-varying...I don't think that "In R the time-varying covariate approach is harder to implement". I believe you just add an interaction term with time, just as you did in SAS.Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-1275149608391671670.post-47383846005778383612013-09-14T05:00:49.331-04:002013-09-14T05:00:49.331-04:00Is there also a possibility to test the proportion...Is there also a possibility to test the proportionality assumption for a discrete-time hazard model? stat4444https://www.blogger.com/profile/09305393095243604112noreply@blogger.comtag:blogger.com,1999:blog-1275149608391671670.post-45707134734417852502013-08-22T11:12:09.794-04:002013-08-22T11:12:09.794-04:00The assess statement in proc phreg can also be use...The assess statement in proc phreg can also be used for assessing the proportionality assumption.Ken Kleinmanhttps://www.blogger.com/profile/09525118721291529157noreply@blogger.comtag:blogger.com,1999:blog-1275149608391671670.post-50885564340252312802012-05-24T16:18:55.123-04:002012-05-24T16:18:55.123-04:00THANKS A MILLION!THANKS A MILLION!Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-1275149608391671670.post-39323793231703162582011-11-01T14:04:32.646-04:002011-11-01T14:04:32.646-04:00Great post! one question though, isn't it supp...Great post! one question though, isn't it supposed to be weighted Schoenfeld residuals, i.e. "wtressch = schres" instead of "ressch=schres" in the output statement?Anonymousnoreply@blogger.com