mslSROC | R Documentation |
The approach to SROC curve modeling is described in the paper of Moses, Shapiro and Littenberg (1993). It is considered outdated and is included in mada
so that users can reproduce older results and compare different SROC curves.
mslSROC(data = NULL, subset=NULL, TP="TP", FN="FN", FP="FP", TN="TN", fpr = NULL, extrapolate = FALSE, correction = 0.5, correction.control = "all", add = FALSE, lty = 1, lwd = 1, col = 1, ...)
data |
any object that can be converted to a data frame with integer variables for observed frequencies of true positives, false negatives, false positives and true negatives. The names of the variables are provided by the arguments |
TP |
character or integer: name for vector of integers that is a variable of |
FN |
character or integer: name for vector of integers that is a variable of |
FP |
character or integer: name for vector of integers that is a variable of |
TN |
character or integer: name for vector of integers that is a variable of |
subset |
the rows of |
fpr |
Points between 0 and 1 on which to draw the SROC curve. Should be tightly spaced. If set to |
extrapolate |
logical, should the SROC curve be extrapolated beyond the region where false positive rates are observed? |
correction |
numeric, continuity correction applied if zero cells |
correction.control |
character, if set to |
add |
logical, should the SROC curve be added to an existing plot? |
lty |
line type, see |
lwd |
line width, see |
col |
color of SROC, see |
... |
arguments to be passed on to plotting functions. |
Details are found in the paper of Moses, Shapiro and Littenberg (1993).
Besides plotting the SROC, an invisible
list is returned which contains the parameters of the SROC.
Philipp Doebler <philipp.doebler@googlemail.com>
Moses L.E., Shapiro D., & Littenberg B. (1993) “Combining independent studies of a diagnostic test into a summary ROC curve: data-analytic approaches and some additional considerations.” Statistics in Medicine, 12, 1293–1316.
reitsma-class
, talpha
, SummaryPts
## First Example data(Dementia) ROCellipse(Dementia) mslSROC(Dementia, add = TRUE) # Add the MSL-SROC to this plot ## Second Example # Make a fancy plot and look at the coefficients msl_Dementia <- mslSROC(Dementia, col = 3, lwd = 3, lty = 3) msl_Dementia$A2 # intercept on logit SROC space msl_Dementia$B2 # slope on logit SROC space
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