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Novice2 TrackerWed, 17 Jul 2024 10:51:35 GMT2024-07-17T10:51:35ZRe: Repeated measures logistic regression and cox proportional hazards
https://communities.sas.com/t5/SAS-Programming/Repeated-measures-logistic-regression-and-cox-proportional/m-p/826077#M326288
<P>Sorry I should have specified above that the time-dependent covariates are continuous in nature</P>Thu, 28 Jul 2022 23:53:43 GMThttps://communities.sas.com/t5/SAS-Programming/Repeated-measures-logistic-regression-and-cox-proportional/m-p/826077#M326288Novice22022-07-28T23:53:43ZRepeated measures logistic regression and cox proportional hazards
https://communities.sas.com/t5/SAS-Programming/Repeated-measures-logistic-regression-and-cox-proportional/m-p/826076#M326287
<P>Hi All, </P><P>I have two questions (don't know if I should start a separate thread for the other, happy to do so if needed).</P><P>I have a longitudinal dataset where patients were followed up for a number of visits. At each visit they were asked 'did condition x occur in the time since last visit' ie a binary outcome (yes/no).</P><P>1) I am planning to do a competing risks cox proportional hazards model. However, I have a covariate which is related to the outcome. How would I take account of this in the coding? Further, the covariate has a time-specific function ie its value drops in the first few weeks, then stays stable. Would I need to introduce a spline?</P><P>2) I would like to do a logistic regression of said outcome x. Would the outcome from a repeated measures logistic regression be significantly different from standard logistic regression? Again, I think one of the predictors would be the time-varying serum marker mentioned above</P><P>Hope that makes sense, I would be grateful for any input and sample code. </P>Thu, 28 Jul 2022 23:52:01 GMThttps://communities.sas.com/t5/SAS-Programming/Repeated-measures-logistic-regression-and-cox-proportional/m-p/826076#M326287Novice22022-07-28T23:52:01ZExposure-response analysis
https://communities.sas.com/t5/Statistical-Procedures/Exposure-response-analysis/m-p/826072#M40916
<P>Hi All,</P><P>I am doing a study in which I examine whether exposure to an agent (metabolite of a certain drug) can predict a longitudinal outcome in that patient. I am looking at patients in a treatment arm from a trial. Each patient may have taken a different quantity (dose) of the underlying drug. They then had a blood test checking for its active metabolite. Different patients will have different numbers of readings, depending on the duration for which they were in the study (dropped out, died, withdrawal etc) and therefore how many visits and subsequent blood tests they had. I want to see how exposure to the drug influences a longitudinal outcome, which itself is time-varying. What would be the best way to analyze this information? Presently, I have added together the total exposure values over however many visits the patient had, and done simple linear regression with the change in the longitudinal variable. I also calculated average exposure for each patient (total exposure/number of visits) and correlated this with the change in the longitudinal outcome (which itself I regressed over the amount of time patients were in the study). However, I feel this is a bit simplistic and am wondering if there is a better statistical method to analyze this question? At the least I feel I probably need to do some analysis with repeated measures. I hope this makes sense. Grateful for any help.</P>Thu, 28 Jul 2022 23:34:54 GMThttps://communities.sas.com/t5/Statistical-Procedures/Exposure-response-analysis/m-p/826072#M40916Novice22022-07-28T23:34:54Z