ratesci 0.4-0 (2021-12-04)
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. ### In 
tdasci(): 
 
- Default uses skew = TRUE for stratum CIs.
 
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.
 
Other
- Renamed tdas argument to ‘random’.
 
- Removed redundant t2 variable.
 
ratesci 0.3-0 (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)
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.