Help with survival analysis with a landmark period

[Olubunmi Adebiyi]

Hi everyone,

I am new to survival analysis and I will appreciate your help with this analysis. This may be too much to ask but I have looked everywhere without a solution, thank you for your understanding. I am trying to (1.) perform survival analysis with the Kaplan-Meier method on transplant patients with anemia at one year landmark instead of the whole period of the follow-up (the patients were followed for up to 5 years), (2.) perform a cox proportional hazard regression model(using ETHCAT ECMO_TRR), and (3)if possible calculate the competitive risk between GSTATUS(graft failure) and PSTATUS(dead), all based on one year landmark.

A sample of the data is given below. Thank you for your time.

* Example generated by -dataex-. For more info, type help dataex
clear
input float(ID Anemia) double(GTIME PTIME ETHCAT ECMO_TRR TX_YEAR PSTATUS GSTATUS)
1 0 2544 2544 1 0 2013 0 0
1 0 2623 2623 1 0 2013 0 0
1 0    1    1 1 0 2013 1 1
1 0  337  337 4 0 2013 1 1
1 0 2559 2559 2 0 2013 0 0
1 0 2584 2584 1 0 2013 0 0
1 0 2570 2570 5 0 2013 0 0
1 0  702  723 1 0 2013 1 1
1 0 2517 2517 1 0 2013 0 0
1 0 2600 2600 2 0 2013 0 0
1 0 2468 2468 1 0 2013 0 0
1 0 1468 1468 1 0 2013 1 1
1 0 2542 2542 2 0 2013 0 0
1 0 1803 1804 1 0 2013 1 1
1 0 2568 2568 2 0 2013 0 0
1 0 2554 2554 2 1 2013 0 0
1 . 1774 1774 6 0 2013 1 1
1 0 2524 2524 1 0 2013 0 0
1 0 2534 2534 4 0 2013 0 0
1 0 2071 2071 1 0 2013 1 1
1 .    8    8 1 0 2013 1 1
1 0 2531 2531 2 0 2013 0 0
1 0 2498 2498 1 0 2013 0 0
1 0 2484 2484 1 0 2013 0 0
1 0 2591 2591 2 0 2013 0 0
1 0 2555 2555 1 0 2013 0 0
1 0 2525 2525 1 0 2013 0 0
1 0 2558 2558 1 0 2013 0 0
1 0 2548 2548 6 0 2013 0 0
1 0 1461 1461 7 0 2013 1 1
1 0 2573 2573 4 0 2013 0 0
1 1 2563 2563 2 0 2013 0 0
1 0  351  351 1 0 2013 0 1
1 0 2567 2567 2 0 2013 0 0
1 0 2479 2479 1 0 2013 0 0
1 0  141  141 1 1 2013 1 1
1 0 2547 2547 1 0 2013 0 0
1 0 2481 2481 1 0 2013 0 0
1 . 2557 2557 1 0 2013 0 0
1 0 2563 2563 1 0 2013 0 0
1 0 2567 2567 1 0 2013 0 0
1 0 2510 2510 1 0 2013 0 0
1 0 2544 2544 1 0 2013 0 0
1 0 2583 2583 1 0 2013 0 0
1 0   91   91 2 0 2013 1 1
1 0 2534 2534 1 0 2013 0 0
1 0 2522 2522 5 0 2013 0 0
1 0  316  316 2 0 2013 1 1
1 0 2359 2359 1 0 2013 0 0
1 0  549  549 1 0 2013 1 1
1 0 2546 2546 9 0 2013 0 0
1 1 2563 2563 1 0 2013 0 0
1 0   26   26 1 0 2013 1 1
1 0 2675 2675 2 0 2013 0 1
1 0 2235 2235 1 0 2013 0 0
1 0 2491 2491 1 0 2013 0 0
1 0 2524 2524 1 0 2013 0 0
1 0 2238 2238 1 0 2013 0 0
1 0 2531 2531 2 0 2013 0 0
1 0 2586 2586 4 0 2013 0 0
1 0 2238 2238 4 0 2013 0 0
1 0 2552 2552 2 0 2013 0 0
1 0 2137 2137 1 0 2013 0 0
1 0 2545 2545 1 0 2013 0 0
1 0 2578 2578 1 0 2013 0 0
1 0 2553 2553 1 0 2013 0 0
1 0 2549 2549 4 0 2013 0 0
1 0  845  845 1 1 2013 1 1
1 0 2548 2548 4 0 2013 0 0
1 0 2549 2549 2 0 2013 0 0
1 0 2530 2530 4 0 2013 0 0
1 0 2473 2473 1 0 2013 0 0
1 0 2564 2564 1 0 2013 0 0
1 0 2548 2548 4 1 2013 0 0
1 0 2560 2560 2 0 2013 0 0
1 0 2557 2557 1 0 2013 0 0
1 1   55   55 5 1 2013 1 1
1 0 2551 2551 1 0 2013 0 0
1 0 1353 1353 1 0 2013 0 0
1 0 2495 2495 1 0 2013 0 0
1 0 2482 2482 1 0 2013 0 0
1 0 2467 2467 4 0 2013 0 0
1 0 1972 1972 1 0 2013 1 1
1 0 2569 2569 1 0 2013 0 0
1 0 2465 2465 4 0 2013 0 0
1 0 2493 2493 1 0 2013 0 0
1 0  470  473 1 0 2013 1 1
1 0 2117 2117 2 0 2013 0 0
1 0 2535 2535 1 0 2013 0 0
1 0 2187 2187 4 0 2013 0 0
1 0 2544 2544 1 0 2013 0 0
1 0 2487 2487 2 0 2013 0 0
1 0 2191 2191 4 0 2013 0 0
1 0 2576 2576 4 0 2013 0 0
1 0 2467 2467 4 0 2013 0 0
1 0 2582 2582 1 0 2013 0 0
1 0 1203 1203 2 0 2013 1 1
1 0 2525 2525 1 0 2013 0 0
1 0 2526 2526 4 0 2013 0 0
1 0 2303 2303 1 0 2013 0 0
end