4
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The data are organised as long format data. 4 individuals are observed during 4 or 5 days (BCSID is the name of the unique key). Basically, the data describe activities performed during these 4-5 days. START describe the start time of activities and MAINACT the activities.

The data:

data = structure(list(BCSID = c("B10001N", "B10001N", "B10001N", "B10001N", 
 "B10001N", "B10001N", "B10001N", "B10001N", "B10001N", "B10001N", 
 "B10001N", "B10001N", "B10001N", "B10001N", "B10001N", "B10001N", 
 "B10001N", "B10001N", "B10001N", "B10001N", "B10001N", "B10001N", 
 "B10001N", "B10001N", "B10001N", "B10001N", "B10001N", "B10001N", 
 "B10001N", "B10001N", "B10001N", "B10001N", "B10001N", "B10001N", 
 "B10001N", "B10001N", "B10001N", "B10001N", "B10001N", "B10001N", 
 "B10001N", "B10001N", "B10001N", "B10001N", "B10001N", "B10001N", 
 "B10001N", "B10001N", "B10001N", "B10001N", "B10001N", "B10001N", 
 "B10001N", "B10001N", "B10001N", "B10004R", "B10004R", "B10004R", 
 "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", 
 "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", 
 "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", 
 "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", 
 "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", 
 "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", 
 "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", 
 "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", 
 "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", 
 "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", 
 "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", 
 "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", "B10004R", 
 "B10004R", "B10004R", "B10004R", "B10010P", "B10010P", "B10010P", 
 "B10010P", "B10010P", "B10010P", "B10010P", "B10010P", "B10010P", 
 "B10010P", "B10010P", "B10010P", "B10010P", "B10010P", "B10010P", 
 "B10010P", "B10010P", "B10010P", "B10010P", "B10010P", "B10010P", 
 "B10010P", "B10010P", "B10010P", "B10010P", "B10010P", "B10010P", 
 "B10010P", "B10010P", "B10010P", "B10010P", "B10010P", "B10010P", 
 "B10010P", "B10010P", "B10010P", "B10010P", "B10010P", "B10010P", 
 "B10010P", "B10010P", "B10010P", "B10010P", "B10010P", "B10010P", 
 "B10010P", "B10010P", "B10010P", "B10010P", "B10010P", "B10010P", 
 "B10010P", "B10010P", "B10010P", "B10011Q", "B10011Q", "B10011Q", 
 "B10011Q", "B10011Q", "B10011Q", "B10011Q", "B10011Q", "B10011Q", 
 "B10011Q", "B10011Q", "B10011Q", "B10011Q", "B10011Q", "B10011Q", 
 "B10011Q", "B10011Q", "B10011Q", "B10011Q", "B10011Q", "B10011Q", 
 "B10011Q", "B10011Q", "B10011Q", "B10011Q", "B10011Q", "B10011Q", 
 "B10011Q", "B10011Q", "B10011Q", "B10011Q", "B10011Q", "B10011Q", 
 "B10011Q", "B10011Q", "B10011Q", "B10011Q", "B10011Q", "B10011Q", 
 "B10011Q", "B10011Q", "B10011Q", "B10011Q", "B10011Q"), DAY = c("1", 
 "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", 
 "1", "1", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", 
 "2", "2", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", 
 "3", "3", "4", "4", "4", "4", "4", "4", "4", "4", "4", "4", "4", 
 "4", "4", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", 
 "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "2", "2", 
 "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", "2", 
 "2", "2", "2", "2", "2", "2", "2", "2", "3", "3", "3", "3", "3", 
 "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "4", "4", "4", 
 "4", "4", "4", "4", "4", "4", "4", "4", "4", "4", "4", "4", "4", 
 "4", "4", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", "1", 
 "1", "1", "1", "1", "2", "2", "2", "2", "2", "2", "2", "2", "2", 
 "2", "2", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", 
 "3", "3", "3", "3", "4", "4", "4", "4", "4", "4", "4", "4", "4", 
 "4", "4", "5", "5", "1", "1", "1", "1", "1", "1", "1", "1", "1", 
 "1", "1", "2", "2", "2", "2", "2", "2", "2", "2", "3", "3", "3", 
 "3", "3", "3", "3", "3", "3", "3", "3", "3", "3", "4", "4", "4", 
 "4", "4", "4", "4", "4", "4", "4", "5", "5"), START = c("00:00:00", 
 "00:30:00", "10:00:00", "10:05:00", "10:35:00", "11:00:00", "11:03:00", 
 "11:15:00", "14:00:00", "14:30:00", "14:40:00", "14:45:00", "15:05:00", 
 "16:15:00", "17:00:00", "20:00:00", "00:00:00", "09:30:00", "10:00:00", 
 "10:30:00", "10:50:00", "11:15:00", "12:50:00", "14:00:00", "14:20:00", 
 "14:40:00", "15:00:00", "16:00:00", "16:45:00", "00:00:00", "00:30:00", 
 "01:00:00", "10:30:00", "12:00:00", "12:30:00", "12:45:00", "12:50:00", 
 "13:30:00", "14:30:00", "18:30:00", "19:30:00", "20:00:00", "00:00:00", 
 "10:00:00", "10:15:00", "11:00:00", "11:15:00", "12:30:00", "13:00:00", 
 "15:30:00", "16:30:00", "17:00:00", "18:00:00", "21:30:00", "22:30:00", 
 "00:00:00", "07:30:00", "08:10:00", "08:15:00", "08:30:00", "09:30:00", 
 "09:45:00", "11:45:00", "12:45:00", "13:45:00", "14:15:00", "15:15:00", 
 "15:30:00", "15:45:00", "16:30:00", "17:15:00", "17:45:00", "18:00:00", 
 "18:30:00", "20:30:00", "23:20:00", "23:30:00", "00:00:00", "08:00:00", 
 "08:30:00", "09:15:00", "09:30:00", "11:10:00", "13:00:00", "13:30:00", 
 "15:00:00", "16:00:00", "16:30:00", "17:00:00", "17:30:00", "18:00:00", 
 "18:15:00", "18:30:00", "19:00:00", "21:00:00", "21:30:00", "22:00:00", 
 "23:00:00", "23:02:00", "23:15:00", "00:00:00", "07:00:00", "07:30:00", 
 "08:30:00", "08:45:00", "09:45:00", "12:00:00", "13:00:00", "15:00:00", 
 "16:30:00", "17:00:00", "20:45:00", "22:00:00", "22:15:00", "22:45:00", 
 "00:00:00", "07:45:00", "08:00:00", "08:30:00", "09:00:00", "09:10:00", 
 "09:30:00", "11:41:00", "12:15:00", "12:45:00", "13:00:00", "13:30:00", 
 "14:00:00", "17:00:00", "18:00:00", "19:00:00", "20:00:00", "22:30:00", 
 "00:00:00", "06:45:00", "07:50:00", "08:05:00", "08:55:00", "09:00:00", 
 "12:00:00", "13:00:00", "17:00:00", "17:20:00", "18:00:00", "19:00:00", 
 "19:25:00", "23:00:00", "23:25:00", "00:00:00", "00:15:00", "10:00:00", 
 "12:15:00", "18:00:00", "18:10:00", "18:45:00", "19:20:00", "19:45:00", 
 "22:00:00", "22:35:00", "00:00:00", "04:00:00", "10:00:00", "13:00:00", 
 "13:25:00", "16:35:00", "17:15:00", "18:00:00", "19:00:00", "20:00:00", 
 "20:40:00", "21:00:00", "22:50:00", "23:00:00", "23:50:00", "00:00:00", 
 "01:45:00", "06:45:00", "08:00:00", "09:00:00", "12:00:00", "13:00:00", 
 "17:00:00", "18:50:00", "23:15:00", "23:45:00", "00:00:00", "00:15:00", 
 "00:00:00", "07:00:00", "08:00:00", "08:30:00", "08:50:00", "13:30:00", 
 "14:30:00", "17:30:00", "18:00:00", "18:30:00", "19:30:00", "00:00:00", 
 "08:00:00", "09:00:00", "10:30:00", "13:00:00", "18:30:00", "20:00:00", 
 "21:30:00", "00:00:00", "01:00:00", "01:30:00", "09:00:00", "09:30:00", 
 "09:35:00", "10:00:00", "10:30:00", "13:30:00", "14:00:00", "15:30:00", 
 "18:00:00", "22:00:00", "00:00:00", "07:00:00", "07:30:00", "08:00:00", 
 "08:40:00", "12:30:00", "13:30:00", "18:00:00", "18:30:00", "20:00:00", 
 "00:00:00", "00:20:00"), MAINACT = c("-11", "1704", "1302", "1301", 
 "1507", "603", "1301", "101", "502", "1704", "1507", "1404", 
 "8888", "603", "1507", "101", "-11", "1302", "1301", "1507", 
 "704", "101", "1704", "1704", "3102", "1002", "1704", "3101", 
 "101", "-11", "1704", "1302", "1302", "1507", "603", "2902", 
 "3201", "812", "1704", "1704", "3701", "101", "-11", "1302", 
 "1301", "3101", "1001", "1507", "1006", "2101", "2902", "1704", 
 "8888", "1704", "1302", "-11", "1302", "1302", "1507", "1301", 
 "1702", "1001", "2902", "2901", "2101", "2502", "3801", "3001", 
 "3504", "1301", "3503", "3101", "1507", "1301", "2601", "1702", 
 "1302", "1606", "1302", "1301", "502", "101", "101", "1001", 
 "101", "101", "502", "3504", "3101", "2902", "1507", "3702", 
 "1408", "3801", "2902", "2101", "1408", "1302", "1302", "1302", 
 "1606", "1302", "1408", "1503", "2902", "1705", "2701", "2803", 
 "2805", "2902", "3701", "1408", "1301", "1302", "1302", "1606", 
 "1302", "1301", "1507", "603", "4010", "3701", "2101", "4008", 
 "1507", "603", "1301", "2101", "1702", "1507", "3504", "2701", 
 "1302", "-11", "1302", "502", "2502", "102", "101", "103", "101", 
 "502", "502", "1704", "1702", "2902", "1702", "1704", "-11", 
 "1302", "1302", "1702", "2502", "1702", "2902", "1702", "1704", 
 "1702", "2507", "-11", "1702", "1302", "1702", "3601", "1704", 
 "2801", "1702", "2902", "1702", "1704", "3801", "3601", "603", 
 "1302", "1606", "1601", "1302", "502", "101", "103", "101", "502", 
 "2901", "1702", "1704", "-11", "1302", "-11", "1302", "1507", 
 "502", "101", "103", "101", "502", "1704", "701", "1301", "1606", 
 "1302", "502", "301", "301", "1704", "2901", "1702", "-11", "1702", 
 "1302", "1302", "1507", "603", "601", "601", "1507", "603", "1006", 
 "1507", "3201", "-11", "1302", "1507", "1301", "502", "103", 
 "101", "1704", "1301", "1704", "1702", "1302"), eorder2 = c(1, 
 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 1, 2, 3, 
 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 
 10, 11, 12, 13, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 
 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 
 20, 21, 22, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 
 16, 17, 18, 19, 20, 21, 22, 23, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 
 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 
 14, 15, 16, 17, 18, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 
 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 
 7, 8, 9, 10, 11, 12, 13, 14, 15, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 
 11, 1, 2, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 1, 2, 3, 4, 5, 6, 
 7, 8, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 1, 2, 3, 4, 
 5, 6, 7, 8, 9, 10, 1, 2)), .Names = c("BCSID", "DAY", "START", 
 "MAINACT", "eorder2"), row.names = c(NA, 231L), class = "data.frame")

The data look like this:

 BCSID DAY START MAINACT eorder2
28 B10001N 2 16:00:00 3101 12
29 B10001N 2 16:45:00 101 13
30 B10001N 3 00:00:00 -11 1
31 B10001N 3 00:30:00 1704 2
32 B10001N 3 01:00:00 1302 3
33 B10001N 3 10:30:00 1302 4

The variable eorder2 denotes the order of activities per day. The first observation (eorder2 == 1) beginning at midnight (00:00:00) is or should be sleeping.

The missing sleep is denoted -11. What I need to do is to fill this missing sleep with a proxy sleep denoted 1606.

However, I need to specify several conditions for this proxy sleep:

  • I need to exclude DAY 1.
  • I need to "target" the first episode of each day.
  • Finally, I want that the previous last episode is 1302 or 3201 and that the first next episode after -11 is 1302.

Here, for example, Row 220 is a missing that fulfill the conditions. It is the first episode of the day and it is preceded by 3201 and followed by 1302.

 BCSID DAY START MAINACT eorder2
218 B10011Q 3 18:00:00 1507 12
219 B10011Q 3 22:00:00 3201 13
220 B10011Q 4 00:00:00 -11 1
221 B10011Q 4 07:00:00 1302 2
222 B10011Q 4 07:30:00 1507 3

I was thinking doing something like this:

First, specifying some Row conditions:

ep2 = which( data$eorder2 == 1 & # first episode 
 data$DAY != 1 & # not day 1 
 data$MAINACT == '-11') # missing activities

Then fill the missing -11 with a line of code like this:

data[ep2, 'MAINACT'] [ data[ep2-1,'MAINACT'] == '1302' | data[ep2-1,'MAINACT'] == '3201' & data[ep2+1,'MAINACT'] == '1302' ] <- '1606'

Using ep2-1 for targeting the previous episode and ep2+1 the following episode.

This code seems to work. Alternative ideas or corrections are very welcome.

asked Jul 2, 2015 at 15:42
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1 Answer 1

3
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I would first write (or find) a function for shifting a vector x by a given number of observations k. The stat package has a lag function but it only allows to shift in one direction (k has to be >= 0)... Here is such a function that will work both ways, with positive or negative k:

LAG <- function(x, k) {
 if (k == 0) {
 x
 } else if (k > 0) {
 c(rep(NA, k), head(x, -k))
 } else {
 c(tail(x, k), rep(NA, -k))
 } 
}

Then, you can create a boolean vector telling if each row meets all the conditions or not:

need_replace <- with(data, eorder2 == 1 &
 DAY != 1 &
 MAINACT == '-11' &
 LAG(MAINACT, +1) %in% c('1301', '1302') &
 LAG(MAINACT, -1) == '1302')

And finally, do the substitution:

data$MAINACT[need_replace] <- '1606'

A few more comments:

  1. I created a vector of TRUE/FALSE rather than a vector of indices like you did with which. Both work but it is less typing without which.
  2. See that I used with(data, ...) so I did not have to type data$ over and over. This also makes your code shorter and easier to read.
  3. I used %in% instead of two == statements separated by |. That's another good function to know (imagine having many more than two allowed values...)
  4. Be careful that & has higher priority than | so what you had written was equivalent to statement1 | (statement2 & statement 3) which is not the same as what I think you had in mind: (statement1 | statement2) & statement3. Priority rules are documented under ?Syntax.
  5. As it stands, none of the rows in your example data match all the conditions you have specified so please let me know if I misunderstood something, I am sure it will be a simple fix.
answered Jul 3, 2015 at 1:06
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0

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