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!).
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