[程式] SAS 存活分析 cox proportional hazards

看板Statistics作者 (假安靜)時間14年前 (2010/04/13 19:32), 編輯推噓2(2013)
留言15則, 5人參與, 5年前最新討論串1/2 (看更多)
------------------------------------------------------------------------ [軟體程式類別]: sas [程式問題]: cox proportional hazards 資料處理 [軟體熟悉度]: 高(1年以上) [問題敘述]: 目的是根據不同的treatment( trt ) 來做PHREG 然後在同一張圖上畫出兩條 LOG-LOG survival curve 請問有沒有辦法不用 WHERE 這個指令 因為這樣不同的trt必須分開做 然後在用SET把資料彙整 請問有別的指令可以用嗎? [程式範例]: DATA r; INPUT group weeks status wbc sex@@; trt=group-1; IF wbc<2.3 THEN lmh=1; ELSE IF wbc>3 THEN lmh=3; ELSE lmh=2; CARDS; 1 6 1 2.31 0 1 6 1 4.06 1 1 6 1 3.28 0 1 7 1 4.43 0 1 10 1 2.96 0 1 13 1 2.88 0 1 16 1 3.60 1 1 22 1 2.32 1 1 23 1 2.57 1 1 6 0 3.20 0 1 9 0 2.80 0 1 10 0 2.70 0 1 11 0 2.60 0 1 17 0 2.16 0 1 19 0 2.05 0 1 20 0 2.01 1 1 25 0 1.78 1 1 32 0 2.20 1 1 32 0 2.53 1 1 34 0 1.47 1 1 35 0 1.45 1 2 1 1 2.80 1 2 1 1 5.00 1 2 2 1 4.91 1 2 2 1 4.48 1 2 3 1 4.01 1 2 4 1 4.36 1 2 4 1 2.42 1 2 5 1 3.49 1 2 5 1 3.97 0 2 8 1 3.52 0 2 8 1 3.05 0 2 8 1 2.32 0 2 8 1 3.26 1 2 11 1 3.49 0 2 11 1 2.12 0 2 12 1 1.50 0 2 12 1 3.06 0 2 15 1 2.30 0 2 17 1 2.95 0 2 22 1 2.73 0 2 23 1 1.97 1 ; DATA inrisk1; wbc=2.93; PROC PHREG DATA=remission NOPRINT; MODEL weeks*status(0)=wbc; WHERE trt=0; BASELINE COVARIATES=inrisk1 OUT=out10 LOGLOGS=lls/NOMEAN; PROC PHREG DATA=remission NOPRINT; MODEL weeks*status(0)=wbc; WHERE trt=1; BASELINE COVARIATES=inrisk1 OUT=out11 LOGLOGS=lls/NOMEAN; DATA out1; SET out10 (IN=in0) out11 (IN=in1); IF in0 THEN trt=0; ELSE IF in1 THEN trt=1; lls=-lls; PROC PRINT; ----------------------------------------------------------------------------- -- ※ 發信站: 批踢踢實業坊(ptt.cc) ◆ From: 140.119.137.219

04/13 19:34, , 1F
噢 畫出LLS的指令忘記打,不過重點不是那個請見諒
04/13 19:34, 1F

04/13 19:50, , 2F
BY ?
04/13 19:50, 2F

04/13 20:49, , 3F
用過 by 不行耶 print不出來東西
04/13 20:49, 3F

04/13 21:11, , 4F
STRATA可嗎????
04/13 21:11, 4F

04/13 23:19, , 5F
I think what you want is fitting Kaplan-Meier curves for
04/13 23:19, 5F

04/13 23:20, , 6F
different treatment groups.
04/13 23:20, 6F

04/13 23:58, , 7F
not KM , I want PH
04/13 23:58, 7F

04/14 00:45, , 8F
It's not very meaningful because you already impose a
04/14 00:45, 8F

04/14 00:45, , 9F
proportional hazards assumption.
04/14 00:45, 9F

04/14 01:05, , 10F
under that assumption I draw two curve to check if
04/14 01:05, 10F

04/14 01:06, , 11F
it fit the assumption.
04/14 01:06, 11F

04/14 01:33, , 12F
Then what you want is KM curves.
04/14 01:33, 12F

04/14 01:35, , 13F
or other model diagnosis plots. Keep in mind that you
04/14 01:35, 13F

04/14 01:35, , 14F
are dealing with censored data.
04/14 01:35, 14F

01/02 15:05, 5年前 , 15F
proportiona https://noxiv.com
01/02 15:05, 15F
文章代碼(AID): #1Bn5OooQ (Statistics)
文章代碼(AID): #1Bn5OooQ (Statistics)