rdci() now includes the Brown-Li 'Jeffreys' method for binomial RD
(noted to be a superior non-iterative method in Laud & Dane 2014).
orpairci() now includes a second version of the transformed SCAS method,
omitting the 'N-1' adjustment. (The adjusted version previously labelled
'Transformed SCASp' in the output is now labelled 'Transformed SCAS(N-1)').
orpairci() now includes the Transformed Blaker method, produced when
cc is TRUE.
scoreci() and scasci() have improved computation of quadratic solution for
the skewness-corrected score, avoiding spurious results observed in 0.13% of
a simulation exercise (#38, thanks to Vincent Jaquet for reporting the issue
and proposed solution).
orpairci(), rrpairci() and rdpairci() have fixed special cases to avoid
warnings due to negative variance estimate or intervals output as NaN.
orci() now fixed to give CIs for OR instead of RR, and fixed handling of
special cases.
rdci(), rrci() and orci() give a selection of
confidence intervals for each contrast for 2 independent binomial or Poisson
rates.rdpairci(), rrpairci() and orpairci() give
a selection of confidence intervals for each contrast for 2 paired binomial
proportions.scorepairci() and moverpairci() for the
score and MOVER methods, respectively, for paired contrasts, mirroring
scoreci() and moverci() for independent contrasts.pairbinci(),
which is deprecated.rateci():x / n,
instead of an estimate that is consistent with a 0% CI. std_est allows the
user to choose. (#32, thanks to Chelsea Dickens for raising the issue.)cc is TRUE,
and approximately match the corresponding mid-p intervals when cc is FALSE.precis for setting the precision of the exact and mid-p method.pairbinci() is soft-deprecated, and is replaced by scorepairci() for score
methods, moverpairci() for MOVER methods, and rdpairci(), rrpairci and
orpairci() for other methods.rateci() and moverci():rdpairci() with no discordant
pairs).exactci():moverci():clusterpci() for CI and test for a single binomial proportion
from clustered data.pairbinci():skew for skewness correction.bcf for variance bias correction.method_RD, method_RR and method_OR are replaced with method.cc uses a new form of correction for RR giving equivariant intervals. Also
allows consistency with the continuity-corrected McNemar test (or an
intermediate correction of the user's choosing). cctype is deprecated.scaspci():bcf option now implemented for contrast = "p" (default = FALSE).bign allows a different sample size to be used in the bias correction
(used within transformed SCASp method for paired OR in pairbinci, for
consistency with 'N-1' test).scoreci():bcf option now implemented for contrast = "p" (default = FALSE).precis argument is improved for RR and OR contrasts.exactci():pairbinci():cc continuity correction is now available for all methods for all contrasts.cctype controls the type of correction to apply for contrast = "RR".method_RD = "Score_closed" for non-iterative calculation of
the Tango score interval for contrast = "RD". Thanks to Tony Yang for
permission to use the code in his 2013 paper.method_RR = "Score_closed" for non-iterative calculation of
the Tang score interval for contrast = "RR". Thanks to Guogen Shan for
contributing code via email.method_RD = "MOVER" and method_RR = "MOVER".
Also "MOVER_newc" incorporates Newcombe's correlation correction.moverbase, for specifying different versions of the MOVER methods
(Wilson, Jeffreys, midp or SCAS).method_OR options for transformed binomial
methods for OR.scoreci():moverci():type = "wilson".type = "SCAS" and "midp" intervals.scoreci():moverci():moverci() with distrib = "poi" and type = "wilson"]scoreci():tdasci()).Stheta = (p1hat - p2hat * theta) / p2d (see Tang 2020)tdasci():scoreci() corrected for distrib="poi".scoreci() for calculation of stratum CIs with random=TRUE.scoreci() for distrib = "poi" and contrast = "p" (#7).scaspci().rateci() for closed-form calculation of continuity-corrected SCAS.scoreci() for stratified zero scores calculated as NA, resulting in UL = 0. (Thanks to Lidia Mukina for reporting the bug.)scoreci() for OR SCAS method (derived from Gart 1985).pairbinci().scaspci() for non-iterative SCAS methods for single binomial or Poisson rate.rateci() for selected methods for single binomial or Poisson rate.pairbinci() for contrast="OR".moverci() for contrast="p" and type="wilson".scoreci()scoreci().pairbinci() for all comparisons of paired binomial rates.scoreci().scoreci().scoreci() output when stratified = TRUE.moverci().tdasci() wrapper function.moverci().moverci() to posterior median for type = "jeff",
to ensure consistent calculations with informative priors.