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ratesci 1.0.0 (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():

• skew for skewness correction.
• bcf for 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_RR and method_OR are replaced with method.
• 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.
• 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.
• 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():

• 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).

In scoreci():

• bcf option 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 precis argument is improved for RR and OR contrasts.
• For contrast = “RD”, weighting = “Tang” provides optimal test if RR is constant across strata.

Bug fixes

In exactci():

• Corrected duplicate point estimate reported for vector inputs.
• Derive point estimates to match LCL and UCL with level = 0.
• Corrected LCL for Poisson mid-p method.

Other

• Output object column names are updated (lower, est, upper) for consistency and style conformity.
• Tests added to confirm consistency of score methods vs McNemar test.
• Dependence on polynom package removed.
• Edition 3 of testthat implemented.

ratesci 0.5.0 (2025-01-10)

New features

In pairbinci():

• cc continuity correction is now available for all methods for all contrasts.
• cctype controls the type of correction to apply for contrast = “RR”.
• New default 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.
• New default 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.
• Added paired MOVER methods with method_RD = “MOVER” and method_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_OR options 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).

In scoreci():

• Confirmed that continuity corrections for all stratified (fixed-effects) binomial contrasts are consistent with the Mantel-Haenszel correction.
• Updated heterogeneity test to consistently omit non-informative (but non-empty) strata, and output the degrees of freedom.

In moverci():

• Added continuity correction for type = “wilson”.
• Added options for type = “SCAS” and “midp” intervals.
• Standardised output to include lower CL, midpoint, upper CL, in that order.

Bug fixes

In 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 @lovestat.) As a result, double-zero strata need not be excluded when weighting = “MN”.

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() with distrib = “poi” and type = “wilson”]

Other

• Improved documentation of hypothesis tests and continuity corrections, clarifying links to Chi-squared tests and CMH test with selected weights.
• Correction to documentation of default weights for OR.
• Added tests confirming equivalence of iterative and closed-form methods in pairbinci.

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.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.