[FIXED] How to create a (integer or numeric) variable based on a second one, but conditioned to many AND & OR conditions on third variables

Issue

I'm just a little undergrad student and I apologize for my silly question, but I really cannot go further in replicating an article I've found on the Internet. The code is available in Stata, but not in R.

Here the Stata Code, being each line a condition to me met by third variables, so the one I want to create just import the values of the second one.

gen child_care_basic = tuactdur24 if
(tutier1code==3 & tutier2code ==1 & tutier3code==1) |   

[...]

What I tried in R was:

timeuse_2003$CHILD_CARE_BASIC <- NA
timeuse_2003$CHILD_CARE_BASIC[(timeuse_2003$TUTIER1CODE==3 & timeuse_2003$TUTIER2CODE==1 & timeuse_2003$TUTIER3CODE==1) |
                          (timeuse_2003$TUTIER1CODE==3 & timeuse_2003$TUTIER2CODE==1 & timeuse_2003$TUTIER3CODE==1) |
                          (timeuse_2003$TUTIER1CODE==3 & timeuse_2003$TUTIER2CODE==1 & timeuse_2003$TUTIER3CODE==8) |
                          (timeuse_2003$TUTIER1CODE==3 & timeuse_2003$TUTIER2CODE==1 & timeuse_2003$TUTIER3CODE==9) |
                          (timeuse_2003$TUTIER1CODE==3 & timeuse_2003$TUTIER2CODE==1 & timeuse_2003$TUTIER3CODE==10) |
                          (timeuse_2003$TUTIER1CODE==3 & timeuse_2003$TUTIER2CODE==1 & timeuse_2003$TUTIER3CODE==11) |
                          (timeuse_2003$TUTIER1CODE==3 & timeuse_2003$TUTIER2CODE==1 & timeuse_2003$TUTIER3CODE==12) |
                          (timeuse_2003$TUTIER1CODE==3 & timeuse_2003$TUTIER2CODE==1 & timeuse_2003$TUTIER3CODE==99) |
                          (timeuse_2003$TUTIER1CODE==3 & timeuse_2003$TUTIER2CODE==3) |
                          (timeuse_2003$TUTIER1CODE==4 & timeuse_2003$TUTIER2CODE==1 & timeuse_2003$TUTIER3CODE==1) |
                          (timeuse_2003$TUTIER1CODE==4 & timeuse_2003$TUTIER2CODE==1 & timeuse_2003$TUTIER3CODE==8) |
                          (timeuse_2003$TUTIER1CODE==4 & timeuse_2003$TUTIER2CODE==1 & timeuse_2003$TUTIER3CODE==9) |
                          (timeuse_2003$TUTIER1CODE==4 & timeuse_2003$TUTIER2CODE==1 & timeuse_2003$TUTIER3CODE==10) |
                          (timeuse_2003$TUTIER1CODE==4 & timeuse_2003$TUTIER2CODE==1 & timeuse_2003$TUTIER3CODE==10) |
                          (timeuse_2003$TUTIER1CODE==4 & timeuse_2003$TUTIER2CODE==1 & timeuse_2003$TUTIER3CODE==10) |
                          (timeuse_2003$TUTIER1CODE==4 & timeuse_2003$TUTIER2CODE==1 & timeuse_2003$TUTIER3CODE==10) |
                          (timeuse_2003$TUTIER1CODE==4 & timeuse_2003$TUTIER2CODE==3 & timeuse_2003$TUTIER3CODE==10) |
                          (timeuse_2003$TUTIER1CODE==17 & timeuse_2003$TUTIER2CODE==3 & timeuse_2003$TUTIER3CODE==10) |
                          (timeuse_2003$TUTIER1CODE==17 & timeuse_2003$TUTIER2CODE==4 & timeuse_2003$TUTIER3CODE==10) |
                          (timeuse_2003$TUTIER1CODE==17 & timeuse_2003$TUTIER2CODE==4 & timeuse_2003$TUTIER3CODE==1)
                          ]<- timeuse_2003$TUACTDUR24 

The problem is, I only got NAs in the entire column.

Again, I apologize for such a basic question, but I just tried a lot of different things and nothing worked, so I decided to ask you guys outta of my beginner's box.

Thank you in advance.

Fabricio

Solution

You can follow the pattern below to create a new column with a subset of values based on your business logic.

timeuse_2003 = data.frame(
    TUACTDUR24 = c(10.1, 20.2, 30.3, 40.4, 50.5),
    TUTIER1CODE = c(3, 4, 3, 4, 3),
    TUTIER2CODE = c(1, 1, 1, 3, 3))

timeuse_2003

  TUACTDUR24 TUTIER1CODE TUTIER2CODE
1       10.1           3           1
2       20.2           4           1
3       30.3           3           1
4       40.4           4           3
5       50.5           3           3

selection = timeuse_2003$TUTIER1CODE==3 & timeuse_2003$TUTIER2CODE==1
timeuse_2003$CHILD_CARE_BASIC = NA
timeuse_2003$CHILD_CARE_BASIC[selection] = timeuse_2003$TUACTDUR24[selection]

timeuse_2003

  TUACTDUR24 TUTIER1CODE TUTIER2CODE CHILD_CARE_BASIC
1       10.1           3           1             10.1
2       20.2           4           1               NA
3       30.3           3           1             30.3
4       40.4           4           3               NA
5       50.5           3           3               NA

Answered By - BigFinger

Answer Checked By - Timothy Miller (PHPFixing Admin)