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is_it_normal()
provides the ability
for users of traumar
to get descriptive statistics on one
or more numeric variables, with optional normality tests, and diagnostic
plots (for one variable only). Grouping functionality is also supported
in is_it_normal()
to conduct exploratory data analysis of
one or more variables within zero or more groups.seqic_indicator_1()
seqic_indicator_2()
seqic_indicator_3()
seqic_indicator_4()
seqic_indicator_5()
seqic_indicator_6()
seqic_indicator_7()
seqic_indicator_8()
seqic_indicator_9()
seqic_indicator_10()
seqic_indicator_11()
seqic_indicator_12()
seqic_indicator_13()
is_it_normal()
nonlinear_bins()
to make the
percent
column calculate correctly when groups were not
introduced.probability_of_survival()
, nonlinear_bins()
,
rmm()
, and rm_bin_summary()
using more helpful
data.nonlinear_bins()
when the argument Ps_col
does not follow the expected
distribution of the calculated probability of survival, and/or a sample
size too small to calculate bins is passed to the function, including
when passed to rmm()
and
rm_bin_summary()
.air
package through the
RStudio IDE.trauma_case_mix()
,
trauma_performance()
, nonlinear_bins()
,
rmm()
, and rm_bin_summary()
to provide
improved messaging related to missings in Ps_col
and
outcome_col
.outcome
argument was removed from
trauma_performance()
to remove ambiguity in the nature of
the outcome_col
values. Only values of
TRUE/FALSE
and 1/0
are accepted.diagnostics
argument was removed from
trauma_performance()
to make the user interface smoother.
Instead of providing guidance via outputs to the console, users are
encouraged to seek assistance with interpreting results via the source
academic literature and the package documentation.trauma_performance()
will no longer provide a pivoted
output as a default. Users can elect to pivot the outputs as needed in
their workflows.rmm()
and rm_bin_summary()
now have a new
argument bootstrap_ci
that allows a user to elect to use
the bootstrap CIs, or not. bootstrap_ci
defaults to
TRUE
in order to better support backward
compatibility.nonlinear_bins()
, rmm()
, and
rm_bin_summary()
.
group_vars = NULL
applies the functions to the
entire dataset without subgrouping.rmm()
outputs longer, setting
pivot = TRUE
will work when group_vars
is
invoked by pivoting longer with the grouping context.NA
handling in rmm()
and
rm_bin_summary()
.nonlinear_bins()
by replacing its internal
for
loop with dplyr
functions, enhancing
accuracy and efficiency without introducing breaking changes.rmm()
and rm_bin_summary()
regarding
probability of survival values Ps_col < 0
and
Ps_col > 1
. Now, these functions will throw an error if
probability of survival values are Ps_col < 0
or
Ps_col > 1
.nonlinear_bins()
function has improved data
validation for the Ps_col
variable.probability_of_survival()
function.rmm()
rm_bin_summary()
nonlinear_bins()
trauma_case_mix()
trauma_performance()
rmm()
rm_bin_summary()
nonlinear_bins()
impute()
normalize()
season()
weekend()
pretty_number()
pretty_percent()
small_count_label()
stat_sig()
theme_cleaner()
%not_in%
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.