r - 使用一个数据集上一列中的日期设置一年范围(向前)，以在 R 中与 id 匹配的不同数据集上查找日期

Question

我有两个数据集，(dt1) 一个带有“开始”日期，每个 ID 最多两个条目(因为这些是 L 或 R 眼手术的条目)和一个 (dt2) 第二个数据库，其中包含多个日期之前和之后开始日期。这些不仅限于眼科手术，还包括任何其他医疗保健就诊。我想在我的数据集中所有 id 的手术 L 和 R 的开始日期的一年内寻找一个事件。如果他们有结果，我想通过偏向性来匹配他们。如果他们没有，那么在一年内最后一次访问时没有侧向匹配(lat)。先前的结果只是开始日期之前的结果或“事件”的数量，先前结果的总和。

id   lat year status       date
1    le   18      1 2018-07-06
1    re   11      1 2011-04-12
2    le   15      0 2015-01-10
2    re   11      0 2011-07-20
3    NA   10      1 2010-02-18
3 bilat   13      1 2013-09-26



    id   lat outcome       date year
 1:  1    NA       0 2015-07-06   15
 2:  1    le       0 2019-04-03   19
 3:  1    le       1 2019-04-30   19
 4:  1    re       1 2011-07-14   11
 5:  1    re       1 2015-09-10   15
 6:  1    re       1 2008-07-14    8
 7:  2    NA       0 2015-11-10   15
 8:  2    re       0 2012-04-23   12
 9:  2    NA       0 2015-02-18   15
10:  2    57       0 2008-12-01    8
11:  3    57       0 2014-01-15   14
12:  3    NA       0 2014-02-21   14
13:  3 bilat       1 2014-02-28   14

我希望决赛 table 看起来像这样

id lat year status       date outcome   end_date prior_outcome
1  le   18      1 2018-07-06       1 2019-04-30             3
1  re   11      1 2011-04-12       1 2011-07-14             1
2  le   15      0 2015-01-10       0 2015-11-10             0
2  re   11      0 2011-07-20       0 2012-04-23             0
3  NA   10      1 2010-02-18       0       <NA>             0
3 bilat 13      1 2013-09-26       1 2014-02-28             0

这是数据集的代码

 dates <- as.Date(c("2018-07-06","2011-04-12",
                   "2015-01-10","2011-07-20",
                   "2010-02-18","2013-09-26"))
dt1 <- data.table(id=c(1,1,2,2,3,3),
                  lat=c("le","re","le","re","NA", "bilat"),
                  year= c(18, 11,15,11,10,13),
                  status=status <- c(1,1,0,0,1,1),
                  date= dates)

dates2 <- as.Date(c('2015-07-06',
                    '2019-04-03',
                    '2019-04-30',
                    '2011-07-14',
                    '2015-09-10',
                    '2008-07-14',
                    '2015-11-10',
                    '2012-04-23',
                    '2015-02-18',
                    '2008-12-01',
                    '2014-01-15',
                    '2014-02-21',
                    '2014-02-28' ))
dt2 <- data.table(id=c(1,1,1,1,1,1,2,2,2,2,3,3,3),
                  lat=c("NA","le","le","re","re","re","NA","re","NA","57", "57", "NA","bilat"),
                  outcome = c(0,0,1,1,1,1,0,0,0,0,0,0,1),
                          date= dates2, year= c(15,19,19,11,15,08,15,12,15,08,14,14,14))
                          

我尝试过这样的事情，但它在原始集合中不起作用，因为我在开始日期之前得到结果，所以我假设代码可能在这个小数据集中工作，但实际上，它在某种程度上是不正确的。

#left join dt1 and dt2
dt1_dt2 <- left_join( dt2,dt1, by= "id", suffix=c("2event","1op"))

#filter does with outcome after date1 
dt1_dt2$tdiff = difftime(dt1_dt2$date2event,dt1_dt2$date1op, units= "days")
dt1_dt2 = dt1_dt2 %>% filter(outcome== 1) %>% 
  filter(tdiff <= 365, tdiff >= 0)
         

#then match on the closest date since farthest was not supported 
setDT(dt1)
setDT(dt1_dt2)
setkey(dt1, id, lat) #key set to match
dt3 <- dt1_dt2[, date2, by =.(id, lat2), roll ="nearest"] #how can I keep all variables?
dt3 = unique(dt3, by = c("id", "date2","lat2"))

Answer 1

更新的答案

# construct complete data
da <- merge(dt1,dt2,by=c("id","lat"),all.x = TRUE,suffixes = c("_start","_end"))
# select desired columns => add tdiff ==> replace outcome == NA with 0
da2 <- da[,.(id,lat,year_start,status,date_start,outcome,date_end)][
  , tdiff := as.numeric( difftime(date_end, date_start, units= "days"))][, outcome:=fifelse(is.na(outcome),0,outcome)]

# add flag to show whether the part of da2 (id,lat) also appears in dt2
setkey(da2,id,lat)
setkey(dt2,id,lat)
da2[,flag:=FALSE][dt2,flag:=TRUE]

# get desired result
dt_desired <- da2[0 <= tdiff & tdiff <= 365 | lat == "NA" | is.na(date_end)]
rows <- dt_desired[flag==FALSE & outcome == 0]
# fill with last event's date_end within one year
dt_desired[flag==FALSE & outcome == 0]$date_end <- dt2[,.SD,keyby=.(id,date)][,.SD[.N],by=id][rows,date]
dt_desired[as.numeric( difftime(date_end, date_start, units= "days")) > 365]$date_end <- NA

结果 :

   id lat year_start status date_start outcome   date_end tdiff  flag
1:  1  le         18      1 2018-07-06       1 2019-04-03   271  TRUE
2:  1  re         11      1 2011-04-12       1 2011-07-14    93  TRUE
3:  2  le         15      0 2015-01-10       0 2015-11-10    NA FALSE
4:  2  re         11      0 2011-07-20       0 2012-04-23   278  TRUE
5:  3  57         13      0 2013-09-26       1 2014-01-15   111  TRUE
6:  3  NA         10      1 2010-02-18       0       <NA>    NA FALSE

原答案
根据您的代码，我得到的结果接近您想要的结果。请检查是否正确。

dt1_dt2 <- left_join( dt2,dt1, by= "id", suffix=c("2event","1op"))
# add column tdiff, equal to your method
dt1_dt2[, tdiff := as.numeric( difftime(date2event, date1op, units= "days") )]

# select desired columns
dt1_dt2[0 <= tdiff & tdiff <= 365, 
        .(id,lat1op,year1op,status,date1op,outcome,date2event)]

我和你的结果之间的差异位于第 5 行。
从你提供的数据中，我找不到任何 结束日期与 不适用 .
至于 优先结果 ，你没有展示如何计算它。我认为这不是主要问题。