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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.
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