[R] Monte Carlo simulation for ratio and its CI

[Marna Wagley]

Dear Bert,
Thank you very much for the response.
I did it manually but I could not put them in a loop so that I created the
table manually with selecting the rows randomly several times. Here what I
have done so far, please find it. I want to create the table 100 times and
calculate its mean and CI from those 100 values. If anyone can give me some
hint to make a loop, that would be great. I am very grateful with your help.
Thanks,

library(dplyr)

library(plyr)

dat<-structure(list(v1 = c(NA, TRUE, TRUE, TRUE, TRUE, TRUE, NA, TRUE,

NA, NA, TRUE, TRUE, TRUE, TRUE, NA, NA, TRUE, TRUE), v2 = c(TRUE,

NA, NA, NA, NA, TRUE, NA, NA, TRUE, TRUE, NA, TRUE, TRUE, NA,

NA, TRUE, TRUE, NA), v3 = c(TRUE, TRUE, NA, TRUE, TRUE, NA, NA,

TRUE, TRUE, NA, NA, TRUE, TRUE, TRUE, NA, NA, TRUE, NA)), .Names = c("v1",

"v2", "v3"), class = "data.frame", row.names = c(NA, -18L))


ratio1 <- with(dat, sum(v1,na.rm = TRUE)/sum(v3,na.rm=TRUE))

ratio2 <- with(dat, sum(v2,na.rm = TRUE)/sum(v3,na.rm=TRUE))

#

A1<-sample_n(dat1, 16)# created a table with selecting a 16 sample size
(rows)

A1.ratio1<-with(A1, sum(v1,na.rm = TRUE)/sum(v3,na.rm=TRUE))

A1.ratio2 <- with(A1, sum(v2,na.rm = TRUE)/sum(v3,na.rm=TRUE))

A1.Table<-data.frame(Ratio1=A1.ratio1, Ratio2=A1.ratio2)

#

A2<-sample_n(dat1, 16)

A2.ratio1<-with(A2, sum(v1,na.rm = TRUE)/sum(v3,na.rm=TRUE))

A2.ratio2 <- with(A2, sum(v2,na.rm = TRUE)/sum(v3,na.rm=TRUE))

A2.Table<-data.frame(Ratio1=A2.ratio1, Ratio2=A2.ratio2)

#

A3<-sample_n(dat1, 16)

A3.ratio1<-with(A3, sum(v1,na.rm = TRUE)/sum(v3,na.rm=TRUE))

A3.ratio2 <- with(A3, sum(v2,na.rm = TRUE)/sum(v3,na.rm=TRUE))

A3.Table<-data.frame(Ratio1=A3.ratio1, Ratio2=A3.ratio2)

#

##..............

# I was thinking to repeat this procedure 100 times and calculate the ratio

A100<-sample_n(dat1, 16)

A100.ratio1<-with(A100, sum(v1,na.rm = TRUE)/sum(v3,na.rm=TRUE))

A100.ratio2 <- with(A100, sum(v2,na.rm = TRUE)/sum(v3,na.rm=TRUE))

A100.Table<-data.frame(Ratio1=A100.ratio1, Ratio2=A100.ratio2)

#

Tab<-rbind(A1.Table, A2.Table, A3.Table, A100.Table)


#Compute the mean for each ratio

Ratio1<-mean(Table1[,1])

Ratio2<-mean(Table1[,2])


summary <- ddply(subset(Tab), c(""),summarise,

               N    = length(Tab),

               mean.R1 = mean(Ratio1, na.rm=T),

               median.R1=median(Ratio1, na.rm=T),

               sd.R1   = sd(Ratio1, na.rm=T),

               se.R1   = sd / sqrt(N),

               LCI.95.R1=mean.R1-1.95*se.R1,

               UCI.95.R1=mean.R1+1.95*se.R1,



               mean.R2 = mean(Ratio2, na.rm=T),

               median.R2=median(Ratio2, na.rm=T),

               sd.R2   = sd(Ratio2, na.rm=T),

               se.R2   = sd / sqrt(N),

               LCI.95.R2=mean.R2-1.95*se.R2,

               UCI.95.R2=mean.R2+1.95*se.R2

               )

 summary



On Mon, Mar 25, 2019 at 4:50 PM Bert Gunter <bgunter.4567 using gmail.com> wrote:

>
> > ratio1 <- with(dat, sum(v1,na.rm = TRUE)/sum(v3,na.rm=TRUE))
> > ratio1
> [1] 1.2
>
> It looks like you should spend some more time with an R tutorial or two.
> This is basic stuff (if I understand what you wanted correctly).
>
> Also, this is not how a "confidence interval" should be calculated, but
> that is another off topic discussion for which stats.stackexchange.com is
> a more appropriate venue.
>
> Cheers,
> Bert
>
> Bert Gunter
>
> "The trouble with having an open mind is that people keep coming along and
> sticking things into it."
> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
>
>
> On Mon, Mar 25, 2019 at 4:31 PM Marna Wagley <marna.wagley using gmail.com>
> wrote:
>
>> Hi R User,
>> I was trying to calculate ratios with confidence interval using Monte
>> Carlo
>> simulation but I could not figure it out.
>> Here is the example of my data (see below), I want to calculate ratios
>> (dat$v1/dat$v3 & dat$v2/dat$v3) and its confidence intervals using a 100
>> randomly selected data sets.
>> Could you please give me your suggestions how I can estimate ratios with
>> CI?
>> I will be very grateful to you.
>> Sincerely,
>>
>> MW
>> ---
>> dat<-structure(list(v1 = c(NA, TRUE, TRUE, TRUE, TRUE, TRUE, NA, TRUE,
>>
>> NA, NA, TRUE, TRUE, TRUE, TRUE, NA, NA, TRUE, TRUE), v2 = c(TRUE,
>>
>> NA, NA, NA, NA, TRUE, NA, NA, TRUE, TRUE, NA, TRUE, TRUE, NA,
>>
>> NA, TRUE, TRUE, NA), v3 = c(TRUE, TRUE, NA, TRUE, TRUE, NA, NA,
>>
>> TRUE, TRUE, NA, NA, TRUE, TRUE, TRUE, NA, NA, TRUE, NA)), .Names = c("v1",
>>
>> "v2", "v3"), class = "data.frame", row.names = c(NA, -18L))
>>
>>
>> ratio1<-length(which(dat$v1 == "TRUE"))/length(which(dat$v3 == "TRUE"))
>>
>> ratio2<-length(which(dat$v2 == "TRUE"))/length(which(dat$v3 == "TRUE"))
>>
>>
>> Thanks
>>
>>         [[alternative HTML version deleted]]
>>
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