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ipwpoint(): weights.trunc was wrong
whenever trunc was set. The lower and upper quantiles were
recycled across rows, so every truncated weight was replaced by one of
the two bounds. Weights are now clipped at the trunc and
1 - trunc quantiles, and weights between the bounds are
left unchanged.ipwtm() with family = "multinomial" or
"ordinal": predicted probabilities are now matched to the
observed exposure by level name rather than by column position. 1.3.1
stopped with an error for a two-level exposure, or when an exposure
level did not occur among the rows used to fit the models.ipwpoint() with family = "multinomial" now
works for a two-level exposure; 1.3.1 stopped with an error (“Observed
exposure levels do not match fitted probability levels”).numerator)
with family = "multinomial" and "ordinal" in
ipwpoint(). These failed in 1.3.0 and were fixed by the
1.3.1 rewrite (#3, @adcascone).ipwtm() with type = "first" and
family = "multinomial" / "ordinal": a switch
is again defined as the first record at any level other than the lowest
level in the whole data set, as in ipw <= 1.2.1.1. In 1.3.1 the
reference level was chosen separately for each subject.ipwtm() now checks that all model variables exist and
contain no missing values, and that a binomial/survival exposure is
coded 0/1, with clear error messages instead of errors from inside
glm() / coxph().ipwtm() with family = "survival" now stops
with a clear message when a formula contains strata(),
which is not supported.num.mod /
den.mod no longer carry an inlined copy of the data in
their call, so printing them is readable again.ipwpoint() and ipwtm() share one set of
internal helpers for argument checks, formula construction, probability
extraction and truncation.import() of whole packages; all calls
use pkg::fun. methods is no longer
imported.data-raw/make-regression-fixtures.R).ipwtm, ipwpoint,
ipwplot, tstartfun):
as.formula()) to
eliminate fragile eval(parse(text = ...)) string
manipulations.ipwtm into dedicated family modeling
engines (binomial, survival,
multinomial, ordinal,
gaussian).survival::basehaz and
stats::approx.tstartfun to use safe column evaluation and
direct vector lag logic (c(-1, t[-length(t)])).testthat suite to 3rd edition specs, expanding
coverage for multinomial, ordinal,
gaussian, unstabilized models, weight truncation, and
invalid parameter rejection.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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