r-确定重叠日期的存在和范围由ID编号 - 两个数据帧

Question

我有两个数据帧，如下所示。它们的长度不相等：

library(lubridate)
id <- c(1, 2, 2, 2, 2, 3, 4, 4, 6, 7, 7, 7, 7, 7, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 9, 9, 9, 9,
    10, 10, 10, 11, 11, 12, 13, 14, 15, 15, 5451396, 5451396, 5451396, 5451396, 5451396)
admDt <- ymd(c("2000-02-24", "2000-04-30", "2000-06-06", "2001-01-29", "2004-06-10", "2001-05-21",
           "2000-01-25", "2000-04-18", "2000-01-14", "1991-10-06", "1992-02-25", "2000-05-17",
           "2003-06-06", "2009-02-16", "2000-01-23", "2000-03-10", "2000-04-05", "2000-06-16",
           "2000-07-04", "2000-07-27", "2001-01-19", "2002-08-16", "2002-09-19", "2004-04-17",
           "2005-08-02", "2005-09-21", "2006-07-10", "2000-02-24", "2000-05-05", "2000-08-29",
           "2001-01-24", "2000-01-27", "2000-03-09", "2000-04-15", "2000-03-20", "2002-11-13",
           "2000-06-28", "2000-07-02", "2000-06-13", "1999-12-27", "2008-09-10", "2000-04-09",
           "2000-06-01", "2002-11-25", "2006-08-04", "2006-10-07"))
sepDt <- ymd(c("2000-02-25", "2000-05-25", "2000-06-06", "2001-02-15", "2004-07-12", "2001-06-01",
           "2000-01-31", "2000-04-20", "2000-01-31", "1991-11-07", "1992-03-26", "2000-05-31",
           "2003-06-17", "2009-02-23", "2000-03-06", "2000-03-17", "2000-04-06", "2000-06-28",
           "2000-07-17", "2000-07-31", "2002-04-19", "2002-09-11", "2003-05-06", "2004-05-03",
           "2005-08-31", "2006-05-29", "2009-06-19", "2000-03-09", "2000-05-06", "2000-09-12",
           "2001-01-24", "2000-02-15", "2000-03-17", "2000-04-16", "2000-04-20", "2002-12-05",
           "2000-07-27", "2000-08-15", "2000-06-22", "2000-02-12", "2008-09-17", "2000-05-26",
           "2000-08-29", "2003-02-24", "2006-09-22", "2006-11-10"))
adm <- data.frame(id, admDt, sepDt)
id <- c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 5451396)
birthDt <- ymd(c("1971-07-22", "1982-08-09", "1976-01-30", "1972-02-03", "1958-05-26", "1979-05-24",
             "1971-11-03", "1980-02-05", "1978-06-08", "1969-10-14", "1962-01-01", "1977-03-09",
             "1952-01-24", "1974-12-16", "1956-05-05", "1963-07-16"))
dxDt <- ymd(c("2000-02-24", "2000-04-30", "2000-03-03", "2000-01-31", "2000-06-20", "2000-12-13",
          "2000-05-14", "2000-01-23", "2000-03-09", "2000-02-15", "2000-05-01", "2000-06-30",
          "2000-08-15", "2000-06-22", "2000-01-27", "2000-06-01"))
admPreDx <- c("No", "No", "No", "Yes", "No", "No", "No", "No", "Yes", "Yes","Yes", "Yes", "Yes",
          "Yes", "Yes", "Yes")
admPreDxNbr <- c(0, 0, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1)
admPreDxDur <- c(0, 0, 0, 6, 0, 0, 0, 0, 14, 19, 20, 2, 31, 9, 31, 25)
admPostDx <- c("Yes", "Yes", "No", "No", "No", "No", "Yes", "Yes", "No", "Yes", "No", "Yes", "No",
           "No", "Yes", "Yes")
admPostDxNbr <- c(1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 3)
admPostDxDur <- c(1, 25, 0, 0, 0, 0, 14, 31, 0, 6, 0, 27, 0, 0, 16, 31)
admDx <- data.frame(id, birthDt, dxDt, admPreDx, admPreDxNbr, admPreDxDur, admPostDx, admPostDxNbr,
                admPostDxDur)

> head(adm)
  id      admDt      sepDt
1  1 2000-02-24 2000-02-25
2  2 2000-04-30 2000-05-25
3  2 2000-06-06 2000-06-06
4  2 2001-01-29 2001-02-15
5  2 2004-06-10 2004-07-12
6  3 2001-05-21 2001-06-01
> head(admDx)
  id    birthDt       dxDt admPreDx admPreDxNbr admPreDxDur admPostDx admPostDxNbr admPostDxDur
1  1 1971-07-22 2000-02-24       No           0           0       Yes            1            1
2  2 1982-08-09 2000-04-30       No           0           0       Yes            1           25
3  3 1976-01-30 2000-03-03       No           0           0        No            0            0
4  4 1972-02-03 2000-01-31      Yes           1           6        No            0            0
5  5 1958-05-26 2000-06-20       No           0           0        No            0            0
6  6 1979-05-24 2000-12-13       No           0           0        No            0            0

实际数据集范围从10,000到1,000,000以上。

adm中的每一行是指离散的医院入院。注意：id是患者的ID号，而admDt和sepDt分别指入学日期。有些患者有多次入院。

admDx中的每一行是指一个患者：id是患者的ID号（与adm中提供的ID相一致），而birthDt和dxDt分别是患者的出生和诊断日期。

。 。

我正在进行一些纵向/时间序列分析，并想确定在诊断前和诊断后不同的时间段内患者是否住院。为了简洁起见，这个问题与诊断前后一个月有关。理想情况下，我想：

• 创建一个二分法变量（"是"/"否"），表明给定的患者是否在此期间在医院里度过了一段时间（即，我不担心他们是在时间段之前被录取吗？他们在偏移后被排出）
• 计算每个患者在此期间住院的次数
• 计算每个患者在此期间住院的持续时间（天数）

我在几天内审查了许多帖子（例如，r时间段重叠，通过ID加入数据范围和重叠的日期范围，如何显示事件发生在r中的两个日期之间）；但是，它们似乎都没有结合我感兴趣的三个方面（计算重叠日期之间的时间；多个数据帧；按"组" [或个人]）。

）。

我是R的新手，在循环和更先进的配方方面几乎没有经验。似乎可以从"DescTools"软件包中使用foverlaps，lubridate或%overlaps%；但是，我不确定如何构建相关公式。

任何帮助都将不胜感激！

编辑＃1：

而 @sirallen的建议在提供的示例中的特定时间段工作时，sum(pmin(dxDt, sepDt) - pmax(admDt, dxDt)), by = "id"返回了我的真实数据集中的不准确值（例如，有一天有多个入院时间的患者有一天[2000-01-25" - " 2000-01据报道，-26"]在医院里度过了零天。这对我来说似乎很奇怪，因为该代码似乎被用来回答类似的例子。此问题与我有几个重叠的日期范围有关？

下面的代码通过确定a）患者是否在医院和b）入院数量来提供了我问题的前两个部分的更直接途径：

：

library(data.table)
setDT(adm)
setDT(admDx)[, (4:9) := NULL]
#Period bounds
admDx[, `:=`(dxDtN1 = dxDt %m-% months(1), dxDtP1 = dxDt %m+% months(1))]
#Hospitalised in the month preceding diagnosis
admDx <- adm[admDx, on = .(id, admDt < dxDt, sepDt > dxDtN1), .N, by = .EACHI]
admDx[, `:=` (admPreDx = factor(ifelse(N > 0, "Yes", "No")))]

但是，PMIN/PMAX代码仍然不起作用，返回负值：

admDx[, `:=` (birthDt = birthDt, dxDt = dxDt, dxDtN1 = dxDt %m-% months(1), dxDtP1 = dxDt %m+% months(1))]
admDx[, `:=` (admPreDxDur=as.numeric(sum(pmin(dxDt, adm$sepDt) - pmax(dxDtN1, adm$admDt)))), by = "id"]
admDx <- select(admDx, admPreDx, N, admPreDxDur)

> head(admDx)
   admPreDx N admPreDxDur
1:       No 0      -28573
2:       No 0      -27160
3:       No 0      -28366
4:      Yes 1      -29357
5:       No 0      -26701
6:       No 0      -28044

编辑＃2

测试其他情况后，问题是：PMIN/PMAX可能与> vs >=的使用有关：当使用>时，返回了正确的Dur值；但是，当使用>=时，Dur返回值为0。

如何适应此代码以使我能够计算到诊断日期和包括诊断日期的天数？

Answer 1

我们可以使用 data.table中的非Equi加入（> = V1.9.8）：

library(data.table)
setDT(adm)
setDT(admDx)[, (4:9):= NULL]
# period bounds
admDx[, `:=`(dxDtLo=dxDt-31, dxDtHi=dxDt+31)]
# hospitalized pre-dxnosis?
admDx = adm[, .(id, admDt, sepDt, dxDt=admDt, dxDtLo=sepDt)][admDx,
  on=.(id, dxDt < dxDt, dxDtLo > dxDtLo)]
admDx[, admPreDx:= as.numeric(!is.na(admDt))]
admDx[, `:=`(admPreDxNbr=sum(admPreDx), admPreDxDur=as.numeric(
  sum(pmin(dxDt,sepDt) - pmax(admDt,dxDtLo)))), by='id']
admDx[, c('admDt','sepDt'):= NULL]
# hospitalized post-dxnosis?
admDx = adm[, .(id, admDt, sepDt, dxDtHi=admDt, dxDt=sepDt)][admDx,
  on=.(id, dxDtHi < dxDtHi, dxDt > dxDt)]
admDx[, admPostDx:= as.numeric(!is.na(admDt))]
admDx[, `:=`(admPostDxNbr=sum(admPostDx), admPostDxDur=as.numeric(
  sum(pmin(sepDt,dxDtHi) - pmax(dxDt,admDt)))), by='id']
admDx[, c('admDt','sepDt'):= NULL]
admDx[is.na(admDx)] = 0
admDx = unique(admDx)[, c('dxDtLo','dxDtHi'):= NULL]
> admDx
#          id       dxDt    birthDt admPreDx admPreDxNbr admPreDxDur admPostDx admPostDxNbr admPostDxDur
#  1:       1 2000-02-24 1971-07-22        0           0           0         1            1            1
#  2:       2 2000-04-30 1982-08-09        0           0           0         1            1           25
#  3:       3 2000-03-03 1976-01-30        0           0           0         0            0            0
#  4:       4 2000-01-31 1972-02-03        1           1           6         0            0            0
#  5:       5 2000-06-20 1958-05-26        0           0           0         0            0            0
#  6:       6 2000-12-13 1979-05-24        0           0           0         0            0            0
#  7:       7 2000-05-14 1971-11-03        0           0           0         1            1           14
#  8:       8 2000-01-23 1980-02-05        0           0           0         1            1           31
#  9:       9 2000-03-09 1978-06-08        1           1          14         0            0            0
# 10:      10 2000-02-15 1969-10-14        1           1          19         1            1            8
# 11:      11 2000-05-01 1962-01-01        1           1          20         0            0            0
# 12:      12 2000-06-30 1977-03-09        1           1           2         1            1           27
# 13:      13 2000-08-15 1952-01-24        1           1          31         0            0            0
# 14:      14 2000-06-22 1974-12-16        1           1           9         0            0            0
# 15:      15 2000-01-27 1956-05-05        1           1          31         1            1           16
# 16: 5451396 2000-06-01 1963-07-16        1           1          25         1            1           31