Hi All,
I have a function that is used with data frames having multiple id's
per row and it aggregates the data down to 1 id per row. It also
randomly selects one of the within-id values of a variable (mod),
which often differ within-id. Assume this data frame (below) is much
larger and I want to repeat this function, say 100 times, and then
derive the mean values of r over those 100 replications. Is there an
easy way to do this? What about in more complex situations
where the output is r, var(r), wi, etc, and a mean of all output is
desired, e.g.:
id<-c(1,1,1,rep(4:12))
n<-c(10,20,13,22,28,12,12,36,19,12, 15,8)
r<-c(.68,.56,.23,.64,.49,-.04,.49,.33,.58,.18, .6,.21)
mod1<-factor(c(1,2,2, rep(c(1,2,3),3)))
mod2<-c(1,2,15,rep(3,9))
datas<-data.frame(id,n,r,mod1,mod2)
# intermediate level fuction (courtesy of Hadley Wickham):
pick_one <- function(x) {
if (length(x) == 1) return(x)
sample(x, 1)
}
# Function that I want replicated 100 times:
cat_sum1 <- function(meta, mod) {
m <- meta
m$mod <- mod
meta <- ddply(m, .(id), summarize, r = mean(r), n=mean(n), mod =
pick_one(mod))
meta$z <- 0.5*log((1 + meta$r)/(1-meta$r))
meta$var.z <- 1/(meta$n-3)
meta$wi <- 1/meta$var.z
return(meta)
}
# output from 1 run:
cat_sum1(datas,datas$mod1)
id r n mod z var.z wi
1 1 0.49 14.33333 2 0.53606034 0.08823529 11.33333
2 4 0.64 22.00000 1 0.75817374 0.05263158 19.00000
3 5 0.49 28.00000 2 0.53606034 0.04000000 25.00000
4 6 -0.04 12.00000 3 -0.04002135 0.11111111 9.00000
5 7 0.49 12.00000 1 0.53606034 0.11111111 9.00000
6 8 0.33 36.00000 2 0.34282825 0.03030303 33.00000
7 9 0.58 19.00000 3 0.66246271 0.06250000 16.00000
8 10 0.18 12.00000 1 0.18198269 0.11111111 9.00000
9 11 0.60 15.00000 2 0.69314718 0.08333333 12.00000
10 12 0.21 8.00000 3 0.21317135 0.20000000 5.00000
Is there a way that I could get this to run multiple times
(internally) and then output in a similar format as above but with the
mean values from the multiple runs?
Any help is much appreciated!
AC
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