Subsetting problem data, 2

The variables are actually L11, L12, L21, L22, ... , L81, L82. Would just
creating a vector c(L11,... ,L82) be fine? (I'm about to try it, but I
wanted to check to see if that was going to be a big issue).

On Thu, Jul 19, 2012 at 3:27 PM, Rui Barradas <ruipbarradas at sapo.pt> wrote:

Hello,

Try the following. The data is your example of Patient A through E, but
from the output of dput().

dat <- structure(list(Patient = structure(c(1L, 1L, 1L, 1L, 1L, 2L,
2L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 5L, 5L, 5L), .Label = c("A",
"B", "C", "D", "E"), class = "factor"), Cycle = c(1L, 2L, 3L,
4L, 5L, 1L, 2L, 1L, 3L, 4L, 5L, 1L, 2L, 4L, 5L, 1L, 2L, 3L),
     V1 = c(0.4, 0.3, 0.3, 0.4, 0.5, 0.4, 0.4, 0.9, 0.3, NA, 0.4,
     0.2, 0.5, 0.6, 0.5, 0.1, 0.5, 0.4), V2 = c(0.1, 0.2, NA,
     NA, 0.2, NA, NA, 0.9, 0.5, NA, NA, 0.5, 0.7, 0.4, 0.5, NA,
     0.3, 0.3), V3 = c(0.5, 0.5, 0.6, 0.4, 0.5, NA, NA, 0.9, 0.6,
     NA, NA, NA, NA, NA, NA, NA, NA, NA), V4 = c(1.5, 1.6, 1.7,
     1.8, 1.5, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
     NA), V5 = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA,
     NA, NA, NA, NA, NA, NA)), .Names = c("Patient", "Cycle",
"V1", "V2", "V3", "V4", "V5"), class = "data.frame", row.names = c(NA,
-18L))

dat

nms <- names(dat)[grep("^V[1-9]$", names(dat))]
dd <- split(dat, dat$Patient)
fun <- function(x) any(is.na(x)) && any(!is.na(x))
ix <- sapply(dd, function(x) Reduce(`|`, lapply(x[, nms], fun)))

dd[ix]
do.call(rbind, dd[ix])


I'm assuming that the variables names are as posted, V followed by one
single digit 1-9. To keep the Patients with complete cases just negate the
index 'ix', it's a logical index.
Note also that dput() is the best way of posting a data example.

Hope this helps,

Rui Barradas

Em 19-07-2012 15:15, Lib Gray escreveu:

Hello,

I didn't give enough information when I sent an query before, so I'm
trying
again with a more detailed explanation:

In this data set, each patient has a different number of measured
variables
(they represent tumors, so some people had 2 tumors, some had 5, etc). The
problem I have is that often in later cycles for a patient, tumors that
were originally measured are now missing (or a "new" tumor showed up). We
assume there are many different reasons for why a tumor would be measured
in one cycle and not another, and so I want to subset OUT the "problem"
patients to better study these patterns.

An example:

Patient  Cycle  V1  V2  V3  V4  V5
A  1  0.4  0.1  0.5  1.5  NA
A  2  0.3  0.2  0.5  1.6  NA
A  3  0.3  NA  0.6  1.7  NA
A  4  0.4  NA  0.4  1.8  NA
A  5  0.5  0.2  0.5  1.5  NA

I want to keep patient A; they have 4 measured tumors, but tumor 2 is
missing data for cycles 3 and 4

B  1  0.4  NA  NA  NA  NA
B  2  0.4  NA  NA  NA  NA

I do not want to keep patient B; they have 1 tumor that is measure
consistently in both cycles

C  1  0.9  0.9  0.9  NA  NA
C  3  0.3  0.5  0.6  NA  NA
C  4  NA  NA  NA  NA  NA
C  5  0.4  NA  NA  NA  NA

I do want to keep patient C; all their data is missing for cycle 4 and
cycle 5 only measured one tumor

D  1  0.2  0.5  NA  NA  NA
D  2  0.5  0.7  NA  NA  NA
D  4  0.6  0.4  NA  NA  NA
D  5  0.5  0.5  NA  NA  NA

I do not want patient D, their two tumors were measured each cycle

E  1  0.1  NA  NA  NA  NA
E  2  0.5  0.3  NA  NA  NA
E  3  0.4  0.3  NA  NA  NA

I DO want patient E; they only had one tumor register in Cycle 1, but
cycles 2 and 3 had two tumors.


Thanks for any help!

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