how to calculate time since last dose event? Thanks

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dat = structure(list(ID = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L), DAY = c(1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 30L, 30L, 30L, 30L, 30L, 30L,
30L, 30L, 30L, 30L, 30L, 60L, 60L, 60L, 60L, 60L, 60L, 60L, 60L,
60L, 60L, 60L, 1L, 1L, 1L, 30L, 30L, 30L, 60L, 60L, 60L, 1L,
1L, 30L, 30L, 60L, 60L), TIME = c(0, 0, 1.16, 1.89, 2.88, 3.85,
4.95, 5.94, 8.01, 9.89, 24, 49, 49.5, 696, 696, 696.83, 698.01,
699.02, 700.11, 700.91, 702.06, 703.9, 705.93, 720, 1416, 1416,
1417, 1417.82, 1418.96, 1420.02, 1421.13, 1422.04, 1424.12, 1426.03,
1440, 0, 0, 2.09, 696, 696, 698.14, 1416, 1416, 1417.83, 0, 0,
696, 696, 1416, 1416), AMT = c(".", "50000", ".", ".", ".", ".",
".", ".", ".", ".", ".", "", "", ".", "50000", ".", ".", ".",
".", ".", ".", ".", ".", ".", ".", "50000", ".", ".", ".", ".",
".", ".", ".", ".", ".", ".", "50000", ".", ".", "50000", ".",
".", "50000", ".", ".", "50000", ".", "50000", ".", "50000"),
MDV = c(0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 1L,
0L, 0L, 1L, 0L, 1L, 0L, 1L), EVID = c(0L, 1L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 1L
), II = c(".", "24", ".", ".", ".", ".", ".", ".", ".", ".",
".", "", ".", ".", "24", ".", ".", ".", ".", ".", ".", ".",
".", ".", ".", "24", ".", ".", ".", ".", ".", ".", ".", ".",
".", ".", "24", ".", ".", "24", ".", ".", "24", ".", ".",
"24", ".", "24", ".", "24"), SS = c(".", ".", ".", ".", ".",
".", ".", ".", ".", ".", ".", "", ".", ".", "2", ".", ".",
".", ".", ".", ".", ".", ".", ".", ".", "2", ".", ".", ".",
".", ".", ".", ".", ".", ".", ".", ".", ".", ".", "2", ".",
".", "2", ".", ".", ".", ".", "2", ".", "2"), ADDL = c(".",
"28", ".", ".", ".", ".", ".", ".", ".", ".", ".", "", ".",
".", "29", ".", ".", ".", ".", ".", ".", ".", ".", ".", ".",
"29", ".", ".", ".", ".", ".", ".", ".", ".", ".", ".", "28",
".", ".", "29", ".", ".", "29", ".", ".", "28", ".", "29",
".", "29"), OBS = 1:50), .Names = c("ID", "DAY", "TIME",
"AMT", "MDV", "EVID", "II", "SS", "ADDL", "OBS"), class = "data.frame", row.names = c(NA,
-50L))

For the above dataset, there are 3 subjects, dose event is indicated by AMT >0, MDV=1, EVID=1, but there are II (interdose interval) and ADDL (additional doses) which means last dose time may not be 0 for the records before second record with AMT >0, for example, for ID=1 and record with OBS= 12 ~14, the last dose time should be 48, 48, 672 and time since last dose event for these three records should be 1, 1.5, 24. Basically the dose was give every 24 hrs and totally 89 doses

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关键词：calculate thanks Thank Event Since structure

1. # Following your code
   
2. # dat = structure(list(ID = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, ...
   
3. # Change all data type to numeric for easy operation
   
4. datNew <-
   
5.   with(
   
6.     dat,
   
7.     data.frame(
   
8.       ID   = ID,
   
9.       DAY  = DAY,
   
10.       TIME = TIME,
    
11.       AMT  = as.numeric(gsub("\\.", "", AMT)),
    
12.       MDV  = MDV,
    
13.       EVID = EVID,
    
14.       II   = as.numeric(gsub("\\.", "", II)),
    
15.       SS   = as.numeric(gsub("\\.", "", SS)),
    
16.       ADDL = as.numeric(gsub("\\.", "", ADDL)),
    
17.       OBS  = OBS
    
18.               )
    
19.       )
    
20. 
    
21. # Function to do last observation carried forward - LOCF
    
22. # see http://stackoverflow.com/questions/1782704/propagating-data-within-a-vector/1783275#1783275
    
23. fillInTheBlanks <-
    
24.   function(S) {
    
25.   ## NA in S are replaced with observed values
    
26.   
    
27.   ## accepts a vector possibly holding NA values and returns a vector
    
28.   ## where all observed values are carried forward and the first is
    
29.   ## also carried backward.  cfr na.locf from zoo library.
    
30.   L <- !is.na(S)
    
31.   c(S[L][1], S[L])[cumsum(L)+1]
    
32. }
    
33. 
    
34. # Time of dosing recorded in the dataset
    
35. datNew$*****S <-
    
36.   with(datNew,
    
37.        ifelse(EVID == 1, TIME, NA))
    
38. 
    
39. # LOCF for *****S, II, & ADDL
    
40. datNew$*****S.locf <-
    
41.   with(datNew, unlist(tapply(*****S, ID, fillInTheBlanks)))
    
42. 
    
43. datNew$II.locf <-
    
44.   with(datNew, unlist(tapply(II, ID, fillInTheBlanks)))
    
45. 
    
46. datNew$ADDL.locf <-
    
47.   with(datNew, unlist(tapply(ADDL, ID, fillInTheBlanks)))
    
48. 
    
49. # Time since last dose
    
50. datNew$TSLD <-
    
51.   with(
    
52.     datNew,
    
53.     TIME - *****S.locf - pmin(floor(TIME - *****S.locf) %/% II.locf, ADDL.locf)*II.locf
    
54.       )

复制代码

> # Time of dosing recorded in the dataset
>  
> datNew$*****S <-
Error: unexpected '^' in "datNew$**"
>  
>   with(datNew,
+  
+        ifelse(EVID == 1, TIME, NA))
[1]   NA    0   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA  696   NA   NA   NA   NA   NA   NA   NA   NA   NA   NA 1416   NA   NA   NA   NA
[31]   NA   NA   NA   NA   NA   NA    0   NA   NA  696   NA   NA 1416   NA   NA    0   NA  696   NA 1416

when I change *****S to S, I got below dataset (datNew):, however, for the records with OBS = 11, 24, 35, TSLD should be 24 instead of current 0 in datNew. Thanks for further help in advance.

datNew = structure(list(ID = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L), DAY = c(1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 3L, 3L, 30L, 30L, 30L, 30L, 30L, 30L,
30L, 30L, 30L, 30L, 30L, 60L, 60L, 60L, 60L, 60L, 60L, 60L, 60L,
60L, 60L, 60L, 1L, 1L, 1L, 30L, 30L, 30L, 60L, 60L, 60L, 1L,
1L, 30L, 30L, 60L, 60L), TIME = c(0, 0, 1.16, 1.89, 2.88, 3.85,
4.95, 5.94, 8.01, 9.89, 24, 49, 49.5, 696, 696, 696.83, 698.01,
699.02, 700.11, 700.91, 702.06, 703.9, 705.93, 720, 1416, 1416,
1417, 1417.82, 1418.96, 1420.02, 1421.13, 1422.04, 1424.12, 1426.03,
1440, 0, 0, 2.09, 696, 696, 698.14, 1416, 1416, 1417.83, 0, 0,
696, 696, 1416, 1416), AMT = c(NA, 50000, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, 50000, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, 50000, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 50000,
NA, NA, 50000, NA, NA, 50000, NA, NA, 50000, NA, 50000, NA, 50000
), MDV = c(0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L, 1L, 0L, 0L,
1L, 0L, 1L, 0L, 1L), EVID = c(0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L,
0L, 1L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 1L, 0L, 0L, 1L,
0L, 0L, 1L, 0L, 0L, 1L, 0L, 1L, 0L, 1L), II = c(NA, 24, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 24, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, 24, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
24, NA, NA, 24, NA, NA, 24, NA, NA, 24, NA, 24, NA, 24), SS = c(NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 2, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, 2, NA, NA, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, NA, 2, NA, NA, 2, NA, NA, NA, NA, 2, NA,
2), ADDL = c(NA, 28, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, NA, 29, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 29, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, 28, NA, NA, 29, NA, NA, 29, NA,
NA, 28, NA, 29, NA, 29), OBS = 1:50, S = c(NA, 0, NA, NA, NA,
NA, NA, NA, NA, NA, NA, NA, NA, NA, 696, NA, NA, NA, NA, NA,
NA, NA, NA, NA, NA, 1416, NA, NA, NA, NA, NA, NA, NA, NA, NA,
NA, 0, NA, NA, 696, NA, NA, 1416, NA, NA, 0, NA, 696, NA, 1416
), S.locf = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 696,
696, 696, 696, 696, 696, 696, 696, 696, 696, 696, 1416, 1416,
1416, 1416, 1416, 1416, 1416, 1416, 1416, 1416, 0, 0, 0, 0, 696,
696, 696, 1416, 1416, 0, 0, 0, 696, 696, 1416), II.locf = c(24,
24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24,
24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24,
24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24,
24), ADDL.locf = c(28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28,
28, 28, 28, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29,
29, 29, 29, 29, 29, 29, 29, 29, 28, 28, 28, 28, 29, 29, 29, 29,
29, 28, 28, 28, 29, 29, 29), TSLD = c(0, 0, 1.16, 1.89, 2.88,
3.85, 4.95, 5.94, 8.01, 9.89, 0, 1, 1.5, 24, 0, 0.830000000000041,
2.00999999999999, 3.01999999999998, 4.11000000000001, 4.90999999999997,
6.05999999999995, 7.89999999999998, 9.92999999999995, 0, 24,
0, 1, 1.81999999999994, 2.96000000000004, 4.01999999999998, 5.13000000000011,
6.03999999999996, 8.11999999999989, 10.03, 0, 0, 0, 2.09, 24,
0, 2.13999999999999, 24, 0, 1.82999999999993, 0, 0, 24, 0, 24,
0)), .Names = c("ID", "DAY", "TIME", "AMT", "MDV", "EVID", "II",
"SS", "ADDL", "OBS", "S", "S.locf", "II.locf", "ADDL.locf", "TSLD"
), row.names = c(NA, -50L), class = "data.frame")

I did not test your data but have recently dealt with a similar problem. Here I want to show you the method of how to do it.

1. First you need to extract the dosing event together with the unique ID of the data set, and create a new dataframe.

2. Merge the two data sets by the unique ID, which would give you a column of the dosing time.

3. What's left is pretty straightforward. You can simply do a elementary-school math to calculate the time after dosing.

Hope this helps.