How can i generate the confidence interval in the Hmisc package in R after multiple imputation process?
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I'm going to generate the confidence interval after imputed missing values using Hmisc package in R.
Is there any specific code to generate the confidence interval after the imputation process using Hmisc?
Or is the t.test() function appropriate to be applied to generate the confidence intervals?
This is my current code:
library(Hmisc)
PM <-c(1,4,10,22,15,34,35,55,100,102,103,110,115,116,118,130,135,150,145,200)
data(faithful)
fData <- faithful
XNanData = DataFull = fData
pointsMissing = PM
missIdx = length(pointsMissing)
XNanData[pointsMissing,2] = NA
imputePmm <- aregImpute(~V2 + V1 , data=XNanData, type='pmm',pmmtype=1)
imputation hmisc
asked Nov 11 at 16:47
amjay
66
add a comment |
up vote
0
down vote
favorite
I'm going to generate the confidence interval after imputed missing values using Hmisc package in R.
Is there any specific code to generate the confidence interval after the imputation process using Hmisc?
Or is the t.test() function appropriate to be applied to generate the confidence intervals?
This is my current code:
library(Hmisc)
PM <-c(1,4,10,22,15,34,35,55,100,102,103,110,115,116,118,130,135,150,145,200)
data(faithful)
fData <- faithful
XNanData = DataFull = fData
pointsMissing = PM
missIdx = length(pointsMissing)
XNanData[pointsMissing,2] = NA
imputePmm <- aregImpute(~V2 + V1 , data=XNanData, type='pmm',pmmtype=1)
imputation hmisc
asked Nov 11 at 16:47
amjay
66
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I'm going to generate the confidence interval after imputed missing values using Hmisc package in R.
Is there any specific code to generate the confidence interval after the imputation process using Hmisc?
Or is the t.test() function appropriate to be applied to generate the confidence intervals?
This is my current code:
library(Hmisc)
PM <-c(1,4,10,22,15,34,35,55,100,102,103,110,115,116,118,130,135,150,145,200)
data(faithful)
fData <- faithful
XNanData = DataFull = fData
pointsMissing = PM
missIdx = length(pointsMissing)
XNanData[pointsMissing,2] = NA
imputePmm <- aregImpute(~V2 + V1 , data=XNanData, type='pmm',pmmtype=1)
imputation hmisc
asked Nov 11 at 16:47
amjay
66
I'm going to generate the confidence interval after imputed missing values using Hmisc package in R.
Is there any specific code to generate the confidence interval after the imputation process using Hmisc?
Or is the t.test() function appropriate to be applied to generate the confidence intervals?
This is my current code:
library(Hmisc)
PM <-c(1,4,10,22,15,34,35,55,100,102,103,110,115,116,118,130,135,150,145,200)
data(faithful)
fData <- faithful
XNanData = DataFull = fData
pointsMissing = PM
missIdx = length(pointsMissing)
XNanData[pointsMissing,2] = NA
imputePmm <- aregImpute(~V2 + V1 , data=XNanData, type='pmm',pmmtype=1)
imputation hmisc
imputation hmisc
asked Nov 11 at 16:47
amjay
66
asked Nov 11 at 16:47
amjay
66
asked Nov 11 at 16:47
amjay
66
asked Nov 11 at 16:47
amjay
66
asked Nov 11 at 16:47
amjay
66
66
add a comment |
add a comment |
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