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acc.1test() and acc.paired()
now allow the user (via the argument method.ci)to choose
from a range of differnt types of confidence intervals.tab.paired() and tab.1test()
now allow for data where all subjects are either diseased or
nondiseased.Test 1 is consistently used as the reference test.pv.gs()and pv.wgs(), it is now
diff.ppv <- ppv.2-ppv.1 (instead of
diff.ppv <- abs(ppv.1-ppv.2)), and accordingly for
negative predictive values.pv.prev()) to allow computation
of positive and negative predictive values for different theoretical
prevalences.sesp.gen.mcnemar()) implementing
a generalized McNemar’s test for a joint comparison of sensitivity and
specificity.man/dtcompair-package.rd was
deleted.pv.rpv() now returns the full variance-covariance
matrix (Sigma).ellipse.pv.rpv() generates the data to plot a joint
confidence region for rPPV and rNPV (depends on the ellipse
package) (as in Moskowitz and Pepe, 2006).sesp.rel() calculates relative sensitivity and relative
specificity (with Wald CIs and p-value).tpffpf.rel() calculates relative sensitivity (rTPF) and
relative ‘one minus specificity’ (rFPF) (with Wald CIs and p-value), but
it does not calculate their individual components (ie, TPFs and FPFs);
this function is meant to be used with paired screen-positive designs,
where only rTPF and rFPF are estimable form the data (see Cheng and
Macaluso, 1997 or Alonzo, Pepe, Moskowitz, 2002).sesp.diff.ci (detected by F.
Gimenez - many thanks!).sesp.exactbinom
(detected by J. Swiecicki - many thanks!).These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.