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.