Firstly, I apologize for the vagueness of the title. I have a dataset which contains dichotomous values coded 0 and 1 for a certain variable X. v001 is the subject identifier and the values from v1pc10le8 to v9pc10le8 are the values for X at each of the nine visits. In addition, firstpc10 and lastpc10 signify the first (baseline) and last measurements for X respectively.
v001 firstpc10 lastpc10 v1pc10le8 v2pc10le8 v3pc10le8 v4pc10le8 v5pc10le8 v6pc10le8 v7pc10le8 v8pc10le8 v9pc10le8
1473 28084 0 0 0 <NA> 0 <NA> <NA> 0 0 <NA> <NA>
1474 28089 0 0 <NA> <NA> <NA> 0 <NA> 0 <NA> <NA> <NA>
1475 28102 0 1 <NA> <NA> 0 0 0 0 1 <NA> <NA>
1476 28103 0 1 <NA> <NA> <NA> 0 0 0 0 1 1
1477 28119 0 0 <NA> <NA> <NA> 0 <NA> 0 0 0 <NA>
1478 28184 0 1 <NA> <NA> 0 <NA> <NA> 0 <NA> <NA> 1
1479 28202 1 1 <NA> <NA> 1 <NA> 0 0 0 1 1
1480 28211 0 0 0 <NA> 0 0 <NA> <NA> <NA> <NA> <NA>
1481 28212 0 1 0 <NA> <NA> 1 <NA> <NA> <NA> <NA> <NA>
1482 28213 0 0 <NA> <NA> 0 <NA> <NA> 0 <NA> <NA> <NA>
1483 28214 0 0 <NA> <NA> <NA> 0 0 0 <NA> 1 0
1484 28215 0 0 <NA> <NA> <NA> 0 <NA> 0 0 0 0
1485 28232 0 1 <NA> <NA> 0 <NA> 0 1 <NA> <NA> <NA>
1486 28244 1 1 1 <NA> <NA> <NA> 0 0 0 0 1
1487 28258 0 1 <NA> <NA> <NA> 0 <NA> 0 1 <NA> 1
1488 28281 0 1 <NA> <NA> <NA> 0 0 0 1 <NA> <NA>
1489 28303 0 0 0 <NA> <NA> <NA> <NA> 0 0 0 <NA>
1490 28337 0 1 <NA> <NA> 0 <NA> <NA> 0 <NA> 1 <NA>
1491 28355 1 1 <NA> <NA> 1 <NA> 0 <NA> 0 1 <NA>
1492 29983 0 0 <NA> <NA> <NA> 0 0 <NA> 0 0 0
I want to ignore all the NA and compute a new variable called "change" which has the following values:
1 - if subjects were 0 at baseline and remained 0 throughout
2 - if subjects were 1 at baseline and remained 1 throughout
3 - if subjects were 1 at baseline and changed to 0 (and remained 0 throughout)
4 - if subjects were 0 at baseline and changed to 1 (and remained 1 throughout)
5 - if subjects fluctuated between values of 0 and 1 without a trend (e.g subject #28214) - these are subjects who don't fit in the above 4 catagories
I tried to do this with SPSS and R but I am having huge difficulties and I will greatly appreciate any help. (I have included the dput output from R below).
Thank you!
structure(list(v001 = c(28084, 28089, 28102, 28103, 28119, 28184,
28202, 28211, 28212, 28213, 28214, 28215, 28232, 28244, 28258,
28281, 28303, 28337, 28355, 29983), firstpc10 = c(0, 0, 0, 0,
0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 1, 0), lastpc10 = c(0,
0, 1, 1, 0, 1, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0), v1pc10le8 = c(0,
NA, NA, NA, NA, NA, NA, 0, 0, NA, NA, NA, NA, 1, NA, NA, 0, NA,
NA, NA), v2pc10le8 = c(NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_, NA_real_,
NA_real_, NA_real_), v3pc10le8 = c(0, NA, 0, NA, NA, 0, 1, 0,
NA, 0, NA, NA, 0, NA, NA, NA, NA, 0, 1, NA), v4pc10le8 = c(NA,
0, 0, 0, 0, NA, NA, 0, 1, NA, 0, 0, NA, NA, 0, 0, NA, NA, NA,
0), v5pc10le8 = c(NA, NA, 0, 0, NA, NA, 0, NA, NA, NA, 0, NA,
0, 0, NA, 0, NA, NA, 0, 0), v6pc10le8 = c(0, 0, 0, 0, 0, 0, 0,
NA, NA, 0, 0, 0, 1, 0, 0, 0, 0, 0, NA, NA), v7pc10le8 = c(0,
NA, 1, 0, 0, NA, 0, NA, NA, NA, NA, 0, NA, 0, 1, 1, 0, NA, 0,
0), v8pc10le8 = c(NA, NA, NA, 1, 0, NA, 1, NA, NA, NA, 1, 0,
NA, 0, NA, NA, 0, 1, 1, 0), v9pc10le8 = c(NA, NA, NA, 1, NA,
1, 1, NA, NA, NA, 0, 0, NA, 1, 1, NA, NA, NA, NA, 0)), .Names = c("v001",
"firstpc10", "lastpc10", "v1pc10le8", "v2pc10le8", "v3pc10le8",
"v4pc10le8", "v5pc10le8", "v6pc10le8", "v7pc10le8", "v8pc10le8",
"v9pc10le8"), row.names = 1473:1492, class = "data.frame")
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