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fguerville
Level I

discrete time cox

Hi

Is that possible to perform a Cox Proportional Hazard Regression using discrete time with JMP Pro 12 ?

How to do it with the Fit proportionnal hazard platform ?

In my database, there is one patient per row and i know that the event occured between two visits of the study.

Thanks

Florent

1 ACCEPTED SOLUTION

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jiancao
Staff

Re: discrete time cox

Discrete survival time data is not supported in the Fit Model/Proportional Hazard platform. However, you can run a logistic model after the original survival data is transformed, as shown below.

In this example, the response variable for logisitic regression will be "quit", a 0 and 1 discrete variable, where there are multiple records for those whose survival time (represented by "dur") is more than one year.  Fit logistic to discrete survival time.jpg

Please refer to 7.5.2 in https://data.princeton.edu/wws509/notes/c7s6 for details about the data transformation as well as the analogy between the logistic regression and the discrete time proportional hazards model. 

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3 REPLIES 3
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jiancao
Staff

Re: discrete time cox

Discrete survival time data is not supported in the Fit Model/Proportional Hazard platform. However, you can run a logistic model after the original survival data is transformed, as shown below.

In this example, the response variable for logisitic regression will be "quit", a 0 and 1 discrete variable, where there are multiple records for those whose survival time (represented by "dur") is more than one year.  Fit logistic to discrete survival time.jpg

Please refer to 7.5.2 in https://data.princeton.edu/wws509/notes/c7s6 for details about the data transformation as well as the analogy between the logistic regression and the discrete time proportional hazards model. 

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fguerville
Level I

Re: discrete time cox

Thank you very much, Jiancao.

In your example, how do you use the "censor" data in the logistic regression model ?

Florent.

 

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jiancao
Staff

Re: discrete time cox

You’re welcome. You no longer need that since the values of the binary response variable indicate the censoring status.
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