Description Usage Arguments Details Value Examples
View source: R/psp.univariate.R
Univariate estimation of the relative true positive fraction and relative false positive fraction from a paired screen-positive design. Variance estimation uses
1 | psp.univariate(disease, data, test1, test0)
|
disease |
expression for the outcome |
data |
data-frame of the input data |
test1 |
expression for the new test |
test0 |
expression for the reference test |
This uses the variance estimator from Cheng and Macaluso (1997).
returns a list of class psp.univ
with elements
rTPR
,varlogrTPR
,rFPR
and varlogrFPR
. At
present, the only method available is print.psp.univ
, which
prints the point estimates and confidence intervals.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | ## Not run:
## Prostate cancer example from Pepe and Alonzo (2001):
require(foreign)
ex <- read.dta("http://research.fhcrc.org/content/dam/stripe/diagnostic-biomarkers-statistical-center/files/psa_dre_v2.dta")
psp.univariate(disease=I(d=="yes"), data=ex,
test1=I(psa=="pos"),
test0=I(dre=="pos"))
## We can also do this, albeit less efficiently, using regression models:
summary(fit <- rTPR(I(d=="yes") ~ test,
data = ex,
test1=I(psa=="pos"),
test0=I(dre=="pos")))
summary(fit <- rFPR(I(d=="yes") ~ test,
data = ex,
test1=I(psa=="pos"),
test0=I(dre=="pos")))
## End(Not run)
|
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