The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
For bivariate data the intervention probability bounds,
p10low, p10upp, p11low,
p11upp, and their monotonicity counterparts, are now
clamped to [0, 1], so these and the causal risk ratio bounds derived
from them can no longer fall outside their feasible ranges (matching the
same change in the Stata package). The vectors of individual bound terms
are returned unclamped.
Fixed the ordering of the conditional probabilities passed to the
constraint matrix for trivariate data with a 3-category instrument: the
x=0,y=1 and x=1,y=0 cells within each category of Z were swapped. This
could cause the IV inequality to be wrongly reported as violated on
valid data (and, more rarely, vice versa) and could give incorrect ACE
bounds. Consequently, the first example table from GitHub issue #3 is in
fact compatible with the IV model, so bpbounds() now
correctly reports its IV inequality as satisfied (thanks to @rmtrane for reporting this
in issue #3).
Fixed two typos in the monotonicity ACE bounds for bivariate data
with a binary instrument (monolow4 and
monoupp4 used g00 where g01 was
required), which could give monotonicity bounds that excluded the true
ACE.
Fixed the monotonicity ACE upper bound for trivariate data with a
3-category instrument, which is 1 - p100 - p012 rather than
1 - p100 - p110.
Following these fixes, the bounds for all cases (trivariate and bivariate data, 2- and 3-category instruments, with and without monotonicity) have been verified to equal the sharp bounds computed by linear programming across simulated instrumental variable models. A new test covers the previously untested monotonicity bounds for trivariate data with a 3-category instrument.
Fixes to the Shiny app (runExample()): the default
values for the trivariate data with 3-category instrument example were
transposed relative to their labels, and as labelled violated the IV
inequality; the bivariate 3-category example is now correctly described
as the Mendelian randomization example from the vignette in bivariate
form rather than as hypothetical data; updated the contact email
address; and refactored the server code to use a single reactive
renderPrint().
CRR bounds are now reported as NA when the
corresponding bound on P(Y|do(X=0)) is 0, since the causal risk ratio
bound is then unbounded; the printed summary includes an explanatory
note when this occurs.
bpbounds now requires R 4.1 or later. This is because its soft dependency, tidyr, has a hard dependency, purrr, with this requirement (and tidyr is required for the main example in the vignette).
dplyr removed as a soft dependency and instances
of the magrittr/dplyr pipe, %>%, replaced with the
native pipe, |>.
Fixed incorrect index mapping in
bpbounds_calc_tri_z3(): the x=0,y=1 and x=1,y=0 conditional
probability cells were swapped for each category of Z, giving wrong
bounds for the trivariate 3-category instrument case (thanks @sachsmc).
Tweak formatting of code in helpfile examples and vignette
Bumped minimum required version of R to be at least 4.0.0 because this is now required by evaluate, which is a dependency of knitr.
Bumped version of roxygen2 used to create package documentation
Minor edits to README.md
Additional email address and affiliation edits.
Remove LazyData from
DESCRIPTION.
Update roxygen2 version number in
DESCRIPTION.
Simplify NAMESPACE by not importing functions from other packages.
Improve accompanying pkgdown site
Fixed typo in vignette.
Changed email address.
runExample() to launch the Shiny App included in
./inst/shiny-examples/myapp .R version of our bpbounds Stata command distributed
with Palmer et al., Stata Journal, 2011, 11, 3, 345-367 https://www.stata-journal.com/article.html?article=st0232.
First submission to CRAN.
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.