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.