Description Usage Arguments Value Note Author(s) References Examples
To calculate the sensitivity and specificity for two diagnostic tests in the absence of gold standard using the Bayesian method. The prior information of sensitivity and specificity must be provided.
1 2 3 4 | DTAXG2(group1,group2,
prior.se.group1,prior.sp.group1,
prior.se.group2,prior.sp.group2,
prior.pi,n.sample,n.burnin,SUM)
|
group1 |
vector of 0 and 1, and 1 indicates the positive |
group2 |
vector of 0 and 1, and 1 indicates the positive |
prior.se.group1 |
the prior range of sensitity of group1 |
prior.sp.group1 |
the prior range of specificity of group1 |
prior.se.group2 |
the prior range of sensitity of group2 |
prior.sp.group2 |
the prior range of specificity of group2 |
prior.pi |
the prior range of detection rate |
n.sample |
the number of the Gibbs sampling, defalt is 12000 |
n.burnin |
the number of the burn-in in Gibbs sampling, defalt is 2000 |
SUM |
wheter to return the summary results, defalt is 'TRUE' |
table |
if 'SUM' is TRUE, the Q50, Q2.5, and Q97.5 of sensitivity and specificity will be shown |
PI |
detection rate |
S1 |
sensitivity of group1 |
S2 |
sensitivity of group2 |
C1 |
specificity of group1 |
C2 |
specificity of group2 |
Please feel free to contact us, if you have any advice and find any bug!
Update description:
more functions will be included in 'DATXG' package!
Zhicheng Du<dgdzc@hotmail.com>, Yuantao Hao<haoyt@mail.sysu.edu.cn>
Haiyan Gu, Qiguang Chen. Diagnostic Test Assessment in the Absence of Gold Standard. Zhong Guo Wei Sheng Tong Ji (in Chinese). 1999. 16(4): 203-205.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | group1=c(rep(1,86),rep(0,64))
group2=c(rep(1,27),rep(0,86-27),rep(1,5),rep(0,64-5))
prior.se.group1=c(0.5,0.85)
prior.sp.group1=c(0.8,1)
prior.se.group2=c(0.1,0.5)
prior.sp.group2=c(0.1,0.5)
prior.pi=c(0.66,0.67)
rst=DTAXG2(
group1,
group2,
prior.se.group1,
prior.sp.group1,
prior.se.group2,
prior.sp.group2,
prior.pi,
n.sample=120,
n.burnin=20)
print(rst)
|
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