Thanks, but that produces what I think is an estimated interval.
I really want to use the above formula. I just can't figure out how to
get it to run by the LEAID.
It does require 9 observations to produce an interval, but I was showing a
sample.
Thanks again.
L.A.
Matthew Dowle-3 wrote:
>
> Maybe this (with enough data for a CI) ? :
>
>> Dataset = data.table(Dataset)
>> Dataset[,as.list(wilcox.test(ratio,conf.int=TRUE)$conf.int),by="LEAID"]
> LEAID V1 V2
> [1,] 6307 0.7200000 0.92
> [2,] 8300 0.5678462 0.83
> Warning messages:
> 1: In switch(alternative, two.sided = { :
> Requested conf.level not achievable
>
>
> "L.A." <ro...@millect.com> wrote in message
> news:1261418507079-976414.p...@n4.nabble.com...
>>
>>
>> Well, I'm back again.
>> Thanks for all the help. Besides working, it's helping me begin to
>> understand how these functions work.
>> I still have trouble reading or following the process of a function,
>> which
>> brings my next question:
>>
>> Dataset:
>>
>> LEAID ratio
>> 3 6307 0.7200000
>> 1 6307 0.7623810
>> 2 6307 0.8600000
>> 4 6307 0.9200000
>> 5 8300 0.5678462
>> 7 8300 0.7700000
>> 6 8300 0.8300000
>>
>> Here I want to create confidence intervals around the median. My hang-up
>> now
>> is how to do pbinom() by LEAID.
>>
>> Here's my script.
>>
>> Dataset$obs <- with(Dataset, ave(ratio, LEAID, FUN=function(x)length(x)))
>> obs <-by(Dataset[ , "ratio"], LEAID, length)
>> obsn <-by(Dataset[ , "obs"], LEAID, FUN=function(x)1:max(x))
>>
>> q <- obsn
>> n <- obs
>> pbinom <-pbinom(q, n, .5)
>> pbinom <- with(Dataset, by(obs, LEAID, FUN=function(x)pbinom(q, n, .5)))
>> x <- pbinom
>> x.nolag=x[2:n]
>> x.lag1=x[1:(obs-1)]
>> my.new=cbind(x.nolag,x.lag1)
>> x.fill= cbind(0,0)
>> my.dat.fr=rbind(x.fill, my.new)
>> my.dat.fr
>> pr=1 - (2 * my.dat.fr)
>> cil=ifelse(pr >= .95, Dataset[,"ratio"], 0)
>> cil
>> max=sort(cil)
>> LowerCI=round(max(max),digits=2)
>> LowerCI
>> cn=ifelse(pr >= .95, Dataset[,"ObsNumber"], 0)
>> cmax=sort(cn)
>> c=max(cmax)
>> prb=ifelse(pr >= .95, pr, 999)
>> con=sort(prb)
>> Confidence=min(con)
>> o= n -( c - 1)
>> ch=ifelse (q <= o , Dataset[,"Ratio"], 0)
>> UpperCI=round(max(ch),digits=2)
>> UpperCI
>>
>>
>> I hope your not growing tired of my questions, I try reading all I can
>> find,
>> but I often can't seem understand it until I can actually see it in
>> process.
>> Thanks,
>> L.A.
>> --
>> View this message in context:
>> http://n4.nabble.com/by-function-tp955789p976414.html
>> Sent from the R help mailing list archive at Nabble.com.
>>
>
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