Hello everyone,
I need your help please. I have a big data set with 2000 observations (machines), and some variables like the name, the start date, the age and some characteristics.
These machines have a short lifespan and I have to find why. Which variables have an effect on the lifespan ?
To do this, I need to focus only on machines that have lived longer than 1200 days to find the cause of death.
I had thought of using Cox in this case, but all the machines that have lived more than 1200 days are 'dead', none are alive. For censored data I need to have machines still alive at the end of the study. The ones that are still working are currently between 20d and 600d.
Can I use them for my Cox model knowing that all the machines older than 1200 days are dead?
Thank you in advance for your help
I need your help please. I have a big data set with 2000 observations (machines), and some variables like the name, the start date, the age and some characteristics.
These machines have a short lifespan and I have to find why. Which variables have an effect on the lifespan ?
To do this, I need to focus only on machines that have lived longer than 1200 days to find the cause of death.
I had thought of using Cox in this case, but all the machines that have lived more than 1200 days are 'dead', none are alive. For censored data I need to have machines still alive at the end of the study. The ones that are still working are currently between 20d and 600d.
Can I use them for my Cox model knowing that all the machines older than 1200 days are dead?
Thank you in advance for your help