scoreci()
, improved handling of special cases for MN weighting (#25, thanks to Vincent Jaquet for reporting the issue and proposed solution. Also #27 for RR, thanks to Shangchen Song.)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",
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