Related questions to this have been asked before, but I have tried all
options they gave me unsuccessfully (do.call and unlist).
I start with three lists of summary statistics, 100 elements each, which I
bind together:
statslist <- as.data.frame(cbind (means, vars, mcrs))
I then take 100 samples of this data frame of varying lengths:
stats <- lapply (1:100, function (dummy) {
statslist[sample(nrow(statslist), (sample (10:20, 1, replace = TRUE)),
replace = TRUE),]})
It returns basically what I want:
> stats[[i]]
means vars mcrs
71 1.81 3.832222 2.92725
9 2.56 8.127677 4.734874
91 3.44 9.66303 5.24902
68 0.14 0.1216162 0.008686869
except that:
> is.list(stats[[i]]$means)
[1] TRUE
I don't want this to be a list, because I want to do regressions using the
variable which are in columns, which apparently R won't do if they are in
lists.
I have tried every possible combination of working with do.call, rbind,
as.data.frame, etc to get this into matrix form to no avail.
I have also tried using sapply instead of lapply, but that returns vectors
which again, R doesn't want to do regression on.
Any tips would be very much appreciated, been going around in circles for a
while here.
Edward Waters
PhD Student UNSW
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