R Survival 分析了理解我从数据生成的图形的麻烦-解网

问：

在图中，数据似乎分为两个流，每个流似乎都反映了另一个流，我无法理解结果或为什么会发生这种情况。

你好第一篇文章在这里。

我收集了一个数据文件，其中包含员工、他们的部门以及他们是否辞职的开始日期和结束日期。我的目标是为我的工作场所找到一个生存模式。然而，至少可以说，这张图似乎很奇怪。我正在寻找有关为什么会发生这种情况以及图表告诉我的内容以及我是否犯了任何错误的答案。代码有效，但结果看起来很奇怪。在生存包中的肺部数据集上练习，以重复我的知识。我期待一些看起来更像肺图的东西。

Dag 表示员工在今天之前一直工作的天数（如果他们仍在工作）或他们辞职的日期。 S2 为 0 表示仍在工作，1 表示已退出。 Strata2 是公司的四个不同部门。

library(survival)
library(ggplot2)
library(ggfortify)
library(Hmisc)

SURmodell<-survfit(Surv(Dag, S2) ~Strata2, data = SUR231109)
autoplot(SURmodell)

数据

structure(list(ID = structure(c(2L, 4L, 10L, 18L, 19L, 20L, 28L, 
29L, 31L, 32L, 34L, 36L, 38L, 41L, 42L, 43L, 45L, 46L, 47L, 48L, 
52L, 53L, 55L, 56L, 57L, 58L, 59L, 60L, 64L, 72L, 73L, 77L, 78L, 
79L, 89L, 90L, 91L, 92L, 93L, 94L, 95L, 96L, 98L, 99L, 100L, 
101L, 102L, 103L, 104L, 105L, 106L, 107L, 109L, 121L, 125L, 157L, 
158L, 159L, 160L, 161L, 162L, 163L, 165L, 166L, 167L, 168L, 169L, 
170L, 171L, 189L, 195L, 196L, 198L, 199L, 233L, 234L, 235L, 237L, 
238L, 239L, 244L, 252L, 253L, 254L, 255L, 256L, 257L, 259L, 260L, 
261L, 262L, 263L, 264L, 265L, 266L, 267L, 268L, 270L, 271L, 272L, 
273L, 274L, 288L, 289L, 290L, 297L, 298L, 299L, 300L, 301L, 303L, 
304L, 305L, 306L, 307L, 308L, 309L, 310L, 311L, 312L, 314L, 315L, 
316L, 317L, 318L, 319L, 320L, 321L, 322L, 323L, 324L, 326L, 327L, 
328L, 329L, 330L, 331L, 332L, 333L, 334L, 335L, 350L, 351L, 352L, 
353L, 354L, 355L, 356L, 358L, 359L, 360L, 361L, 362L, 363L, 364L, 
365L, 366L, 367L, 369L, 370L, 371L, 372L, 373L, 374L, 375L, 383L, 
384L, 385L, 386L, 387L, 388L, 389L, 391L, 392L, 393L, 394L, 395L, 
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61L, 62L, 63L, 80L, 81L, 82L, 83L, 84L, 85L, 110L, 111L, 112L, 
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122L, 150L, 151L, 154L, 155L, 156L, 183L, 184L, 187L, 191L, 192L, 
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292L, 294L, 339L, 340L, 341L, 342L, 343L, 344L, 345L, 347L, 348L, 
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522L, 523L, 524L, 525L, 526L, 527L, 528L, 529L, 530L, 533L, 534L, 
539L, 540L, 1L, 152L, 246L, 457L, 470L, 473L, 481L, 489L, 490L, 
491L, 496L, 33L, 37L, 39L, 70L, 71L, 76L, 118L, 120L, 123L, 124L, 
185L, 188L, 194L, 217L, 218L, 220L, 221L, 222L, 223L, 224L, 225L, 
226L, 227L, 228L, 229L, 231L, 232L, 248L, 249L, 250L, 251L, 293L, 
295L, 296L, 415L, 416L, 417L, 418L, 419L, 420L, 422L, 423L, 472L, 
474L, 484L, 494L, 495L, 502L, 505L, 512L, 513L, 514L, 515L, 516L, 
531L, 532L, 535L, 536L, 537L, 538L, 541L, 542L, 543L, 544L, 545L, 
546L, 547L, 548L, 549L, 551L, 552L, 553L, 554L, 555L, 556L, 558L, 
560L, 563L, 564L, 565L, 567L, 568L, 570L, 572L, 573L, 574L, 576L, 
577L, 578L, 580L, 582L, 583L, 584L, 585L, 586L, 5L, 7L, 8L, 9L, 
12L, 13L, 14L, 15L, 17L, 21L, 22L, 23L, 25L, 26L, 27L, 30L, 35L, 
40L, 44L, 49L, 50L, 51L, 54L), .Label = c("Emp1", "Emp10", "Emp100", 
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"Emp511", "Emp512", "Emp513", "Emp514", "Emp52", "Emp53", "Emp534", 
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"Emp541", "Emp542", "Emp543", "Emp544", "Emp545", "Emp546", "Emp547", 
"Emp548", "Emp549", "Emp55", "Emp550", "Emp551", "Emp552", "Emp553", 
"Emp554", "Emp555", "Emp556", "Emp557", "Emp558", "Emp559", "Emp56", 
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"Emp595", "Emp6", "Emp60", "Emp600", "Emp601", "Emp602", "Emp603", 
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"Emp753", "Emp754", "Emp755", "Emp756", "Emp757", "Emp758", "Emp759", 
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"Emp783", "Emp784", "Emp785", "Emp786", "Emp788", "Emp789", "Emp790", 
"Emp791", "Emp792", "Emp793", "Emp800", "Emp814", "Emp815", "Emp824", 
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"Emp955", "Emp96", "Emp967", "Emp968", "Emp969", "Emp97", "Emp970", 
"Emp971", "Emp978", "Emp98", "Emp981", "Emp99", "Emp995", "Emp996", 
"Emp997", "Emp998", "Emp999"), class = "factor"), S2 = structure(c(1L, 
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2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 1L, 2L, 1L, 
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1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = c("0", "1"), class = "factor"), 
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    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 
    3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 
    4L, 4L, 4L, 4L, 4L, 4L, 4L), .Label = c("AVD1", "AVD2", "AVD3", 
    "AVD4"), class = "factor"), Dag = c(373, 87, 80, 73, 73, 
    71, 69, 69, 3, 3, 16, 59, 45, 39, 39, 148, 360, 14, 10, 9, 
    373, 360, 360, 360, 360, 360, 360, 360, 373, 349, 357, 15, 
    99, 191, 91, 94, 105, 205, 235, 263, 263, 263, 263, 264, 
    346, 346, 346, 346, 346, 346, 346, 346, 346, 181, 303, 0, 
    35, 57, 98, 257, 295, 296, 339, 339, 339, 339, 339, 339, 
    339, 336, 78, 296, 332, 332, 145, 312, 312, 140, 311, 311, 
    180, 113, 137, 163, 163, 172, 182, 222, 222, 222, 222, 222, 
    222, 304, 304, 304, 304, 304, 304, 304, 304, 304, 303, 214, 
    302, 28, 43, 51, 52, 69, 69, 74, 144, 172, 288, 297, 297, 
    297, 297, 297, 297, 297, 297, 297, 297, 297, 297, 297, 297, 
    297, 269, 297, 297, 297, 297, 297, 297, 297, 297, 297, 297, 
    166, 36, 134, 162, 290, 290, 290, 290, 290, 290, 290, 290, 
    290, 290, 290, 290, 290, 290, 290, 290, 290, 290, 290, 290, 
    0, 31, 31, 49, 58, 60, 90, 147, 156, 157, 179, 283, 283, 
    283, 283, 283, 283, 283, 283, 283, 283, 283, 283, 283, 283, 
    373, 82, 237, 281, 29, 67, 132, 143, 143, 193, 193, 194, 
    224, 233, 276, 328, 276, 276, 276, 276, 276, 276, 276, 276, 
    276, 276, 371, 46, 158, 269, 269, 269, 269, 269, 269, 266, 
    11, 183, 262, 262, 373, 93, 7, 9, 40, 55, 180, 180, 180, 
    180, 180, 180, 180, 180, 180, 220, 373, 373, 373, 373, 373, 
    373, 373, 373, 373, 373, 373, 373, 373, 373, 373, 373, 373, 
    373, 373, 373, 180, 180, 180, 180, 180, 367, 367, 367, 367, 
    367, 85, 277, 360, 353, 353, 353, 353, 353, 353, 184, 346, 
    346, 346, 150, 158, 181, 343, 343, 343, 343, 343, 343, 343, 
    343, 343, 343, 343, 343, 343, 343, 343, 343, 343, 343, 343, 
    144, 144, 179, 339, 339, 339, 339, 339, 339, 339, 335, 332, 
    332, 332, 81, 325, 325, 325, 324, 155, 241, 241, 325, 333, 
    360, 373, 373, 205, 350, 367, 367, 191, 89, 86, 128, 217, 
    360, 360, 323, 80, 350, 214, 305, 346, 346, 344, 181, 343, 
    343, 343, 343, 207, 339, 287, 335, 335, 335, 106, 200, 332, 
    329, 50, 115, 224, 224, 266, 311, 311, 309, 172, 203, 225, 
    293, 304, 304, 304, 304, 304, 302, 199, 109, 297, 297, 297, 
    297, 297, 245, 296, 255, 295, 109, 290, 290, 290, 289, 171, 
    128, 283, 283, 233, 281, 87, 280, 279, 274, 193, 193, 133, 
    199, 261, 98, 223, 126, 255, 254, 204, 253, 253, 253, 253, 
    248, 247, 244, 241, 241, 241, 106, 238, 72, 170, 183, 234, 
    234, 234, 234, 234, 234, 234, 234, 233, 43, 69, 227, 226, 
    94, 223, 119, 249, 150, 371, 367, 367, 367, 367, 190, 367, 
    367, 228, 360, 360, 358, 358, 103, 345, 345, 273, 343, 338, 
    337, 332, 13, 33, 43, 49, 139, 139, 139, 139, 139, 139, 237, 
    316, 316, 316, 218, 304, 304, 304, 300, 297, 297, 281, 281, 
    281, 281, 107, 281, 214, 281, 267, 266, 260, 253, 253, 248, 
    244, 105, 234, 234, 162, 234, 230, 227, 225, 223, 223, 223, 
    222, 222, 222, 222, 220, 212, 177, 206, 203, 196, 192, 192, 
    192, 192, 192, 192, 185, 178, 178, 178, 171, 171, 161, 64, 
    144, 46, 136, 95, 108, 100, 87, 87, 87, 87, 87, 80, 80, 80, 
    80, 78, 60, 73, 73, 73, 70, 69, 69, 69, 69, 69, 66, 59, 42, 
    24, 8, 8, 3, 2)), row.names = c(NA, -586L), class = c("tbl_df", 
"tbl", "data.frame"))

图表

R 图生存分析

1赞 GuedesBF 11/9/2023

如果没有适当的可重复示例，我们无能为力。请检查如何使 R 可重现示例以及如何提问，并考虑编辑您的问题。我在当前问题中发现的主要问题是缺乏数据。Plase 考虑包括的输出，或者至少是一个有代表性的子集，例如dput(SUR231109)dput(head(SUR231109, 20))

0赞 SMzgr356 11/23/2023

尝试。如果事实证明这是解决方案，将把它移到一个实际的答案。survfit(Surv(Dag, as.numeric(S2)) ~ Strata2, data = SUR231109)

答： 暂无答案

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