ratesci (development version)
New features
In rateci():
- New default point estimate is the “common sense” crude estimate
x / n, instead of an estimate that is consistent with a 0% CI.std_estallows the user to choose. (#32, thanks to Chelsea Dickens for raising the issue.) - New output object containing an alternative formulation of the exact or mid-p interval based on Beta or Gamma distributions. These match Clopper-Pearson and Garwood precisely when
ccisTRUE, and approximately match the corresponding mid-p intervals whenccisFALSE. -
precisfor setting the precision of the exact and mid-p method.
Bug fixes
In rateci() and moverci():
- Permit n=0 to produce output interval as [0, 1] for binomial, or [0, Inf] for Poisson with point estimate displayed as NaN (prevents error in
pairbinci()withmethod= “BP”).
ratesci 1.0.0 (2025-06-20)
CRAN release: 2025-06-20
New features
- New function
clusterpci()for CI and test for a single binomial proportion from clustered data. - Example datasets are now included.
- Improved documentation with pkgdown website & vignettes.
In pairbinci():
-
skewfor skewness correction. -
bcffor variance bias correction. - Default paired RD and RR method changed to new SCAS method (i.e. including skewness correction - manuscript under review).
-
method_RD,method_RRandmethod_ORare replaced withmethod. - Bonett-Price methods for RD and RR (including proposed Jeffreys variant option for RR).
- TDAS method is deprecated.
- Default for MOVER method changed to Jeffreys.
- MOVER calculations now use x/N as point estimate instead of median from the Beta distribution.
-
ccuses 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).cctypeis deprecated. - Default conditional odds ratio method changed to SCASp (with closed-form calculation).
- Output object now includes estimates of p1, p2, phi (correlation) and psi (odds ratio used by Fagerland et al).
- Output object now includes function call.
In scaspci():
-
bcfoption now implemented for contrast = “p” (default = FALSE). -
bignallows a different sample size to be used in the bias correction (used within transformed SCASp method for paired OR inpairbinci, for consistency with ‘N-1’ test).
In scoreci():
-
bcfoption now implemented for contrast = “p” (default = FALSE). - (Note adjusted sample size for bias correction can be achieved by including a non-zero value for n2.)
- ORbias, RRtang, and MNtol arguments renamed as or_bias, rr_tang and mn_tol.
- Implementation of
precisargument is improved for RR and OR contrasts. - For contrast = “RD”, weighting = “Tang” provides optimal test if RR is constant across strata.
ratesci 0.5.0 (2025-01-10)
CRAN release: 2025-01-10
New features
In pairbinci():
-
cccontinuity correction is now available for all methods for all contrasts. -
cctypecontrols the type of correction to apply forcontrast= “RR”. - New default
method_RD= “Score_closed” for non-iterative calculation of the Tango score interval forcontrast= “RD”. Thanks to Tony Yang for permission to use the code in his 2013 paper. - New default
method_RR= “Score_closed” for non-iterative calculation of the Tang score interval forcontrast= “RR”. Thanks to Guogen Shan for contributing code via email. - Added paired MOVER methods with
method_RD= “MOVER” andmethod_RR= “MOVER”. Also “MOVER_newc” incorporates Newcombe’s correlation correction. - Added
moverbase, for specifying different versions of the MOVER methods (Wilson, Jeffreys, midp or SCAS). - Added “jeff” and “wilson”
method_ORoptions for transformed binomial methods for OR. - Confirmed and documented that the 2-sided significance test is equivalent to the McNemar test (with or without continuity correction).
Bug fixes
In moverci():
- Corrected calculation of score intervals for single Poisson rate, using Rao score interval.
- Same correction affects MOVER method for comparison of Poisson rates [i.e.
moverci()withdistrib= “poi” andtype= “wilson”]
ratesci 0.4-0 (2021-12-04)
CRAN release: 2021-12-05
New features
In scoreci():
- MN weighting now iterates to convergence (@jonjvallejo, #20).
- Added optional prediction interval for random effects method (also in
tdasci()). - Added xlim and ylim arguments to control plot output.
- Added sda & fda arguments for optional sparse/full data adjustment when x1 + x2 = 0 or x1 + x2 = n1 + n2 in a stratum.
- Added INV option for weights that omit the variance bias correction.
- Added RRtang argument to apply Tang’s alternative score for RR (recommended for stratified analysis with INV/IVS weights. Experimental for Poisson RR).
Stheta = (p1hat - p2hat * theta) / p2d(see Tang 2020) - Added simplified skewness correction option (causes p-values to be omitted, see Tang 2021 & Laud 2021).
- Introduced warning and plot features for very rare occasions when quadratic skewness correction cannot be calculated due to a negative discriminant.
- p-value suppressed where affected by negative discriminants.
- Changed ORbias default to TRUE (see Laud 2018).
- Changed weighting default to MH for RD & RR, INV for OR (for consistency with CMH test).
- Added hetplot argument to separate heterogeneity plots from score function plot.
- Uninformative strata are now retained in the analysis except if:
- contrast = OR with MH weighting;
- contrast = RR with IVS/INV weighting if RRtang = FALSE;
- random = TRUE (needs further evaluation);
- excluded using new option dropzeros = TRUE.
Bug fixes
- MN weighting in
scoreci()corrected for distrib=“poi”. - Fixed bug in
scoreci()for calculation of stratum CIs with random=TRUE. - Fixed bug in
scoreci()for distrib = “poi” and contrast = “p” (#7). - Fixed finite precision bug in
scaspci(). - Fixed bug in
rateci()for closed-form calculation of continuity-corrected SCAS. - Fixed bug in
scoreci()for stratified zero scores calculated as NA, resulting in UL = 0. (Thanks to Lidia Mukina for reporting the bug.) - Fixed variable plot ranges for vectorised inputs.
ratesci 0.3-0 (2018-02-15)
CRAN release: 2018-02-15
New features
- Added bias correction in
scoreci()for OR SCAS method (derived from Gart 1985). - Added score methods (Tango & Tang) as default for paired binomial RD and RR in
pairbinci(). - Added transformed mid-p method for paired OR for comparison with transformed SCAS.
- Added
scaspci()for non-iterative SCAS methods for single binomial or Poisson rate. - Added
rateci()for selected methods for single binomial or Poisson rate.
Bug fixes
- Fixed bug in
pairbinci()for contrast=“OR”. - Fixed bug in
moverci()for contrast=“p” and type=“wilson”. - Corrected error in cc for stratified SCAS method for OR.
- Clarified documentation regarding continuity corrections.
- Set Stheta to 0 if |Stheta|<cc in
scoreci() - Fixed stratified calulations for contrast = “p” in
scoreci().
ratesci 0.2-0 (2017-04-21)
CRAN release: 2017-04-21
New features
- Added
pairbinci()for all comparisons of paired binomial rates. - Added option to suppress warnings in scoreci.
- Added Galbraith plot (for assessing stratum heterogeneity) to
scoreci(). - Added qualitative interaction test to
scoreci(). - Added stratum estimates & CIs to
scoreci()output when stratified = TRUE.
Bug fixes
- Fixed bug for contrast = “p” in
moverci(). - Fixed bug in
tdasci()wrapper function. - Fixed bug for stratified OR.
- Altered adjustment options for boundary cases in
moverci(). - Changed point estimate used in
moverci()to posterior median for type = “jeff”, to ensure consistent calculations with informative priors.
