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nemsqa_binomial_confint()
, a lightweight
wrapper around prop.test()
and binom.test()
for calculating Wilson and exact confidence intervals. This function
eliminates the need for an additional package dependency.
denominator
< 10
are elegant and helpful, and nemsqa_binomial_confit()
handles division by zero cases well.airway_01()
) to
support optional confidence interval calculation.confidence_interval = FALSE
as
the default behavior.results_summarize()
: Enhanced
results_summarize()
to dynamically calculate only the
specified groups, utilizing the previously unused
population_labels
object. This reduces unnecessary
calculations and streamlines function performance.results_summarize()
and summarize_measure()
,
offering clearer usage instructions and examples to enhance the user
experience._population
workhorse functions handling data extraction
and measure_##
wrapper functions streamlining performance
calculations.airway_01()
, airway_05()
,
airway_18()
asthma_01()
, hypoglycemia_01()
,
pediatrics_03b()
respiratory_01()
, respiratory_02()
,
safety_01()
safety_02()
, safety_04()
,
seizure_02()
stroke_01()
, syncope_01()
,
tbi_01()
trauma_01()
, trauma_03()
,
trauma_04()
trauma_08()
, trauma_14()
,
ttr_01()
airway_01_population()
,
airway_05_population()
,
airway_18_population()
asthma_01_population()
,
hypoglycemia_01_population()
,
pediatrics_03b_population()
respiratory_01_population()
,
respiratory_02_population()
,
safety_01_population()
safety_02_population()
,
safety_04_population()
,
seizure_02_population()
stroke_01_population()
,
syncope_01_population()
,
tbi_01_population()
trauma_01_population()
,
trauma_03_population()
,
trauma_04_population()
trauma_08_population()
,
trauma_14_population()
,
ttr_01_population()
results_summarize()
,
summarize_measure()
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.
Health stats visible at Monitor.