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errorbar_width
and linetype
parameters to g_lineplot
..formats
argument to
tabulate_rsp_subgroups
and
tabulate_survival_subgroups
to allow users to specify
formats.riskdiff
argument to
tabulate_rsp_subgroups
and
tabulate_survival_subgroups
to allow users to add a risk
difference table column, and function control_riskdiff
to
specify settings for the risk difference column.tabulate_rsp_subgroups
when
pval
statistic is selected but df
has not been
correctly generated to add p-values to the output table.n_rate
statistic as a non-default option to
estimate_incidence_rate
which returns both number of events
observed and estimated incidence rate.n_unique
statistic as a non-default option to
estimate_incidence_rate
which returns total number of
patients with at least one event observed.estimate_incidence_rate
to work as both an
analyze function and a summarize function, controlled by the added
summarize
parameter. When summarize = TRUE
,
labels can be fine-tuned via the new label_fmt
argument to
the same function.fraction
statistic to the
analyze_var_count
method group.summarize_glm_count()
documentation and all
its associated functions to better describe the results and the
functions’ purpose.d_count_cumulative
parameters as
described in the documentation.g_lineplot
x-axis were
not shown in either plots.a_surv_time
that threw an error when
split only has "is_event"
.g_lineplot
when using only
one group or strata level.get_formats_from_stats
and
get_labels_from_stats
.scale
parameter)
being applied to response but not to rate in h_glm_count
while all distributions have logarithmic link function.decorate_grob
that did not handle well
empty strings or NULL
values for title and footers.g_km
that caused an error when multiple
records in the data had estimates at max time.\n
and
vector behavior that did not cope well with
split_string()
.summary_formats
and summary_labels
.strata
and
cohort_id
arguments to g_lineplot
.h_incidence_rate.R
file.facet_var
to g_lineplot
to allow
plot faceting by a factor variable.label_all
parameter to
extract_survival_biomarkers
and
extract_survival_subgroups
.xticks
, xlim
, and
ylim
arguments to g_lineplot
to allow for
customization of the x and y axes.g_lineplot
legend to follow factor levels set
by users.s_ancova
that prevented statistics from
being printed when arm levels include special characters.decorate_grob
that prevented the right
margins to be respected when adding title and footers decorations.label_all
parameter to
tabulate_survival_biomarkers
and
tabulate_survival_subgroups
, with redirection to the same
parameter in their associated extract_*
functions.h_glm_negbin
to h_glm_count
to
enable count data analysis using a negative binomial model.grade_groups_only
to
count_occurrences_by_grade
to allow users to only display
rows for specified grade groups.df2gg
that converts
data.frame
objects to ggplot
objects.control_surv_med_annot
and
control_coxph_annot
to configure g_km
annotation table sizes/positions.g_km
to output a ggplot
object
instead of a grob
object.g_forest
to output a ggplot
object instead of a grob
object.mean_pval
) updated
from "xx.xx"
to "x.xxxx | (<0.0001)"
.rtable2gg
to clean up appearance of text labels.s_ancova
causing incorrect difference
calculations for arm variables with irregular levels.format_count_fraction_fixed_dp
that did
not have the same print when the fraction was 1 (100%).g_lineplot
causing default labels not to
update according to specified control
settings.NA
values.expect_snapshot_ggplot
to test setup
file to process plot snapshot tests and allow plot dimensions to be
set.ggplot2
3.5.0.individual_patient_plot.R
to
g_ipp.R
.time_unit_input
, time_unit_output
,
na_level
and indent_mod
.summarize_vars
,
control_summarize_vars
, a_compare
,
create_afun_summary
, create_afun_compare
, and
summary_custom
.vdiffr
package from Suggests in DESCRIPTION
file.strat
, to be
renamed to strata
, within the variables
argument to h_rsp_to_logistic_variables
,
h_logistic_mult_cont_df
,
h_odds_ratio_subgroups_df
,
h_coxreg_mult_cont_df
, h_coxph_subgroups_df
,
h_tbl_coxph_pairwise
, extract_rsp_biomarkers
,
extract_rsp_subgroups
,
extract_survival_biomarkers
, and
extract_survival_subgroups
.strat
argument to
s_coxph_pairwise
and replaced it with the
strata
argument.forest_grob
,
forest_dot_line
, forest_viewport
,
vp_forest_table_part
, and grid.forest
functions.h_ggkm
, h_decompose_gg
,
h_km_layout
, h_grob_tbl_at_risk
,
h_grob_median_surv
, h_grob_y_annot
, and
h_grob_coxph
.grob
/grid
related
functions stack_grobs
, arrange_grobs
, and
draw_grob
which are no longer used in
tern
.ref_group_position
function to place the
reference group facet last, first or at a certain position.keep_level_order
split function to retain
original order of levels in a split.level_order
split function to reorder manually
the levels.get_indents_from_stats
to format and
return indent modifiers for a given set of statistics.apply_auto_formatting
to check for "auto"
formats and replace them with
implementation of format_auto
in analyze functions.labels_use_control
to modify
labels with control specifications.tern_default_stats
.count_occurrences
analyze function, summarize_occurrences
.surv_time
for censored
range observations, controlled via the ref_fn_censor
parameter.h_adlb_abnormal_by_worst_grade
to
prepare ADLB data to use as input in
count_abnormal_by_worst_grade
.s_bland_altman
function to assess agreement
between two numerical vectors.rtable2gg
that converts
rtable
objects to ggplot
objects.na_str
globally
with set_default_na_str()
and added
default_na_str()
for all interested functions.ref_group_coxph
parameter to g_km
to
specify the reference group used for pairwise Cox-PH calculations when
annot_coxph = TRUE
.annot_coxph_ref_lbls
parameter to
g_km
to enable printing the reference group in table labels
when annot_coxph = TRUE
.x_lab
parameter to g_lineplot
to
customize x-axis label.g_lineplot
.arm_y
argument.count_by
input in
analyze_num_patients
and
summarize_num_patients
.g_lineplot
.decorate_grob
preventing text wrapping
from accounting for font size.na_str
argument in all
column-wise analysis and tabulation functions.to_string_matrix
to take into account
widths
and other printing parameters.na_str
argument to analyze
&
summarize_row_groups
wrapper functions
count_abnormal
, count_abnormal_by_baseline
,
count_abnormal_by_marked
,
count_abnormal_by_worst_grade
,
count_abnormal_lab_worsen_by_baseline
,
count_cumulative
, count_missed_doses
,
count_occurrences
, count_occurrences_by_grade
,
summarize_occurrences_by_grade
,
summarize_patients_events_in_cols
,
count_patients_with_event
,
count_patients_with_flags
, count_values
,
estimate_multinomial_response
,
estimate_proportion
, h_tab_one_biomarker
,
estimate_incidence_rate
,
logistic_summary_by_flag
, estimate_odds_ratio
,
estimate_proportion_diff
,
test_proportion_diff
, summarize_ancova
,
summarize_change
, summarize_glm_count
,
summarize_num_patients
, analyze_num_patients
,
summarize_patients_exposure_in_cols
,
coxph_pairwise
, tabulate_survival_subgroups
,
surv_time
, and surv_timepoint
.format_count_fraction_lt10
for formatting count_fraction
with special consideration
when count is less than 10.s_summary.logical
output for
count_fraction
when denominator is zero to display as
NA
instead of 0
in tables.analyze_vars_in_cols
to allow character input
to indicate whether nominal time point is post-dose or pre-dose when
applying the 1/3 imputation rule.g_km
causing an error when converting
certain annotation width units.na_level
argument in
s_count_abnormal_by_baseline
, a_summary
,
analyze_vars
, analyze_vars_in_cols
,
compare_vars
, h_map_for_count_abnormal
,
h_stack_by_baskets
, summarize_colvars
,
a_coxreg
, and summarize_coxreg
and replaced it
with the na_str
argument.strata
and cohort_id
parameters renamed to
group_var
and subject_var
respectively in
g_lineplot
and control_lineplot_vars
.imputation_rule
function to apply imputation rule
to data.format_sigfig
to allow for
numeric value formatting by a specified number of significant
figures.tern_default_formats
and tern_default_labels
,
respectively.get_stats
to return methods from given
statistical method groups.get_formats_from_stats
to return formats
and get_labels_from_stats
to return labels for a given set
of statistics."auto"
option for .formats
. It uses
format_auto
to determine automatically the number of
digits.title
argument to h_grob_tbl_at_risk
and annot_at_risk_title
argument to g_km
and
h_km_layout
which allows user to add “Patients at Risk”
title to Kaplan-Meier at risk annotation table.tabulate_rsp_subgroups
to pass sanitation
checks by preventing creation of degenerate subtables.analyze_vars_in_cols
to use caching, allow
implementation of imputation rule via the imp_rule
argument, and allow user to specify cell alignment via the
.aligns
argument.add_rowcounts
to allow addition of row counts
from alt_counts_df
using the alt_counts
argument.gp
argument to g_forest
to control
graphical parameters such as font size.utils_defaults_handling.R
.summary_custom()
and
a_summary()
as a S3
method.p-value
in the discrete
case to pval_counts
.a_summary_internal()
in favor of only one main
a_summary()
.stat_propdiff_ci
function to calculate
proportion/risk difference and CI.riskdiff
argument to functions
count_occurrences
, count_occurrences_by_grade
,
count_patients_with_event
,
count_patients_with_flags
,
analyze_num_patients
, and
summarize_num_patients
.a_summary
to no longer use the
helper function create_afun_summary
.summarize_vars
and
compare_vars
to use the refactored a_summary
function.ungroup_stats
to
ungroup statistics calculated for factor variables, and
a_summary_internal
to perform calculations for
a_summary
.s_count_occurrences_by_grade
so that
“missing” grade always appears as the final level.analyze_vars_in_cols
when categorical data
was used.s_count_occurrences_by_grade
so that
levels are not relabeled when reordering to account for “missing”
grades..N_row
and
.N_col
parameters.df_explicit_na
. Changes in
NA
values should happen externally to tern
functions, depending on users’ needs.create_afun_summary
and
create_afun_compare
.ylim
argument to g_km
to allow the
user to set custom limits for the y-axis.g_km
which checks whether there is
one arm present in the data when annot_coxph
is true.flag_labels
argument to
s_count_patients_with_flags
to enable more label handling
options in count_patients_by_flags
.nested
argument to analyze
wrapper functions count_abnormal
,
count_abnormal_by_baseline
,
count_abnormal_by_marked
,
count_abnormal_by_worst_grade
,
count_abnormal_lab_worsen_by_baseline
,
count_cumulative
, count_missed_doses
,
count_occurrences
, count_occurrences_by_grade
,
count_patients_with_event
,
count_patients_with_flags
, count_values
,
estimate_multinomial_response
,
estimate_proportion
, estimate_incidence_rate
,
estimate_odds_ratio
, estimate_proportion_diff
,
test_proportion_diff
, summarize_ancova
,
summarize_change
, summarize_glm_count
,
analyze_num_patients
, coxph_pairwise
,
surv_time
, and surv_timepoint
.summarize_vars
and
control_summarize_vars
. Renamed into
analyze_vars
and control_analyze_vars
to
reflect underlying rtables
machinery while keeping backward
compatibility with aliases.character
class to
h_coxreg_inter_effect
enabling character
covariates in summarize_coxreg
.time_unit_input
and
time_unit_output
arguments and replaced them with the
input_time_unit
and num_pt_year
, respectively,
in control_incidence_rate
.pairwise
function.a_compare
and replaced it with
a_summary
with argument compare = TRUE
.create_afun_summary
and
create_afun_compare
which are no longer used by
a_summary
and a_compare
respectively.sum(weights)
for
M1mac
installation.g_km
plot “at risk”
annotation tables.analyze_patients_exposure_in_cols
..indent_mods
argument in functions
h_tab_one_biomarker
, h_tab_rsp_one_biomarker
,
h_tab_surv_one_biomarker
, summarize_logistic
,
logistic_summary_by_flag
,
tabulate_rsp_biomarkers
, a_coxreg
,
summarize_coxreg
,
tabulate_survival_biomarkers
, surv_time
,
surv_timepoint
, and cfun_by_flag
.summarize_coxreg
to print covariates in data
rows for univariate Cox regression with no interactions and content rows
otherwise.d_count_abnormal_by_baseline
labels.g_km
and added dynamic scaling of the surv_med
and
coxph
annotation tables, with customization via the
width_annots
argument.split_text_grob
preventing titles and
footnotes from being properly formatted and printed by
decorate_grob
.g_lineplot
preventing the addition of
lines to the plot when midpoint statistic calculations result in
NA
value(s).tern:::tidy.glm
formals to respect
broom:::tidy.default
formals.README
to include installation instructions for
CRAN.has_count_in_cols
,
has_counts_difference
, combine_counts
,
h_tab_rsp_one_biomarker
, arrange_grobs
,
a_count_patients_sum_exposure
, a_coxreg
,
groups_list_to_df
, forest_viewport
.README
to include installation instructions for
CRAN.indent_mod
argument and replaced
it with the .indent_mods
argument in
summarize_num_patients
and
analyze_num_patients
.s_coxreg
and summarize_coxreg
to
work with new analysis function a_coxreg
.section_div
and na_level
arguments
to summarize_vars
.median_range
as a numeric variable statistic
option for summarize_vars
.d_onco_rsp_label
.g_km
function.a_count_patients_sum_exposure
for
summarize_patients_exposure_in_cols
and new analyze
function analyze_patients_exposure_in_cols
.s_proportion_diff
.s_summary
and s_compare
to allow
NA
values in input variables. For factor variables with
NA
s, if na.rm = FALSE
an explicit
NA
level will be automatically added.
na.rm = TRUE
will also consider
"<Missing>"
values and exclude them.na_level
parameter in
s_summary
and s_compare
to align with other
tern
functions. Instead of being a string to consider as
NA
when setting na.rm = TRUE
, it now defines a
string to print in place of NA
values in the output
table.TRTEDTM
in tern
datasets.na_level
argument in
summarize_vars
preventing it from having an effect.lubridate
package for date variables in
tern
datasets..gitignore
and .Rbuildignore
files.footnotes
functions and all related
files.pairwise
function.count_patients_with_flags
functions from
count_patients_with_event.R
to
count_patients_with_flags.R
.summarize_glm_count
function to analyze count
data using a linear model.g_step
.format_fraction_fixed_dp
and
format_count_fraction_fixed_dp
with fixed single decimal
place in percentages.na_level
and labelstr
arguments to
summarize_vars_in_cols
.analyze_num_patients
to include summary at the
beginning that does not repeat when paginating.h_row_first_values
function as a more general
helper function to retrieve first values from specific rows."(n)"
suffix from
unique_count
labels for s_num_patients
.g_km
to annotate with statistics
(annot_stats
) and add corresponding vertical lines
(annot_stats_lines
).s_count_occurrences_by_grade
.summarize_vars_in_cols
to work with
pagination machinery.conf_level
argument to
emmeans::contrast()
in s_ancova
.rtables_access.R
caused by not checking
for specific combinations (also the standard values that were never
used) of column indices and names.count_abnormal_by_grade
.add_rowcounts
that caused all row count
row values to count as zero.h_col_indices
causing an error when
pruning with combination columns.test_proportion_diff
missing argument for
var_labels
.pkgdown
reference..R
files for logistic regression and
cox regression helper functions.analyze_num_patients
to
generate an initial summary so there is no repetition when
paginating.testthat
3rd edition and replaced
applicable tests with snapshot testing.summarize_ancova
examples to use
iris
dataset instead of scda
data.data/
folder and generated cached synthetic
datasets.data/
folder instead of scda
datasets.tern
. These tests are
in internal repo scda.test
.summarize_vars_in_cols
to
analyze_vars_in_cols
to reflect the appropriate
analyze
logic.summary_in_cols
helper
functions.format_xx
.ggplot2
functions/arguments to fix
warnings.forcats::fct_explicit_na
with forcats::fct_na_value_to_level
.wrap_text
function and related
files.footnotes
functions.estimate_proportion
and
estimate_proportion_diff
with relative tests.stat_mean_pval
, a new summary statistic to
calculate the p-value of the mean.mean_se
(mean with standard error) for
summarize_variables
and related functions.Rdpack
for references.DescTools::BinomDiffCI
function within
tern
.summarize_logistic
to specify
which pivoted value to use during analysis.s_coxph_pairwise
to generate log-rank p-value
using original log-rank test instead of Cox Proportional-Hazards
Model.nestcolor
in all examples by adapting
g_km
, g_ipp
, g_waterfall
,
g_step
, g_lineplot
, and
g_forest
.interaction_y
and
interaction_item
in ANCOVA to make the interaction
calculations available.footnotes
to add footnotes to
g_km
.assertthat
to checkmate
checkmate::assert_vector
,
checkmate::assert_set_equal
, and
checkmate::assert_int
to check vector type, length, and
values.checkmate
the
following functions: all_elements_in_ref
,
is_df_with_nlevels_factor
,
is_df_with_no_na_level
, is_proportion_vector
,
is_quantiles_vector
, is_character_or_factor
,
is_nonnegative_count
, is_valid_character
,
assert_character_or_factor
,
assert_equal_length
and
has_tabletree_colnames
.is_proportion
, is_equal_length
,
is_df_with_no_na_level
,
is_df_with_nlevels_factor
, is_variables
,
is_df_with_variables
, is_df_with_factors
,
is_valid_factor
to use assertion logic.as_factor_keep_attributes
.assert_df_with_factors
and
assert_proportion_value
internal functions.assertthat.R
and test-assertthat.R
to utils_checkmate.R
and
test-utils_checkmate.R
.count_abnormal_by_marked
(reference to
abnormal_by_marked
),
count_abnormal_lab_worsen_by_baseline
and
h_adlb_worsen
(reference to
abnormal_by_worst_grade_worsen_from_baseline
),
count_abnormal_by_worst_grade
(reference to
abnormal_by_worst_grade
), to_string_matrix
,
tidy.summary.coxph
, tidy.step
,
surv_timepoint
, (reference to
survival_timepoint
), surv_time
(reference to
survival_time
), coxph_pairwise
(reference to
survival_coxph_pairwise
),
extract_survival_subgroups
and
tabulate_survival_subgroups
(reference to
survival_duration_subgroups
),
extract_survival_biomarkers
and
tabulate_survival_biomarkers
(reference to
survival_biomarkers_subgroups
),
control_summarize_vars
, s_summary
and
a_summary
(reference to summarize_variables
)
and kept the S3 method tree.summarize_patients_exposure_in_cols
,
summarize_num_patients
with s_num_patients
,
s_num_patients_content
,
summarize_num_patients
.count_cumulative
, count_missed_doses
,
count_patients_events_in_cols
,
summarize_colvars
, summarize_change
,
summarize_ancova
,as.rtable
,
color_palette
, add_footnotes
.control_coxreg
,
control_coxph
, control_incidence_rate
,
control_lineplot_vars
, control_surv_time
,
control_surv_timepoint
, control_logisitic
,
control_step
.stat_mean_ci
, stat_median_ci
,
split_cols_by_groups
, explicit_na
,
sas_na
, extract_rsp_subgroups
,
tabulate_rsp_subgroups
,
extract_rsp_biomarkers
,
tabulate_rsp_biomarkers
, keep_rows
,
keep_content_rows
, has_count_in_any_col
,
has_fraction_in_cols
, has_fraction_in_any_col
,
has_fractions_difference
,
test_proportion_diff
, pairwise
,
logistic_regression
, estimate_incidence_rate
,
control_incidence_rate
(reference to
incidence_rate
), cut_quantile_bins
,
estimate_multinomial_rsp
, decorate_grob_set
,
extreme_format
, fit_rsp_step
,
fit_survival_step
, footnotes
,
footnotes-set
, format_count_fraction
,
format_fraction_threshold
,
formatting_functions
, format_fraction
,
combination_function
(S4 method),
compare_variables
(S3 method),
kaplan_meier
._pkgdown.yml
updated, and tern:::
added for tests/examples/vignettes
where present for the following functions:
abnormal_by_marked
)
s_count_abnormal_by_marked
,
a_count_abnormal_by_marked
.abnormal_by_worst_grade_worsen_from_baseline
)
a_count_abnormal_lab_worsen_by_baseline
,
s_count_abnormal_lab_worsen_by_baseline
.abnormal_by_worst_grade
)
s_count_abnormal_by_worst_grade
,
a_count_abnormal_by_worst_grade
.survival_timepoint
)
s_surv_timepoint
, s_surv_timepoint_diff
,
a_surv_timepoint
, a_surv_timepoint_diff
.survival_time
)
s_surv_time
, a_surv_time
.survival_coxph_pairwise
)
s_coxph_pairwise
, a_coxph_pairwise
.survival_duration_subgroups
)
a_survival_subgroups
.count_cumulative
)
s_count_cumulative
, a_count_cumulative
.count_missed_doses
)
s_count_nonmissing
, s_count_missed_doses
,
a_count_missed_doses
.count_patients_events_in_cols
)
s_count_patients_and_multiple_events
,
summarize_patients_events_in_cols
.incidence_rate
)
s_incidence_rate
, a_incidence_rate
.cox_regression_inter
,
decorate_grob_factory
, draw_grob
,
estimate_coef
.summary_labels
, summary_formats
,
s_count_patients_sum_exposure
,
a_change_from_baseline
s_change_from_baseline
,
a_ancova
, s_ancova
,
arrange_grobs
, as_factor_keep_attributes
,
combine_levels
, split_text_grob
,
groups_list_to_df
, s_cox_multivariate
,
is_leaf_table
, a_response_subgroups
,
range_noinf
, has_count_in_cols
,
has_counts_difference
, prop_chisq
,
prop_cmh
, prop_schouten
,
prop_fisher
, s_test_proportion_diff
,
a_test_proportion_diff
, fct_discard
,
fct_explicit_na_if
.stats::ancova
output due to
version inconsistency.NA
coming from rtables
.formatters::var_labels
.prop_diff
functions to respect success responses
(TRUE
values).cut_quantile_bins
.rtables
split functions)s_ancova
causing an error when the first
level of the arm factor is not the control arm.s_abnormal_by_worst_grade
when there is
one PARAM
level.prop_diff_wald
when selecting all
responders, updated tests accordingly.h_ancova
that caused an error when
deselecting all covariates.g_mmrm
.tern:::
)
and added dontrun
to internal function examples.color_palette
and
h_set_nest_theme
in favor of
nestcolor::color_palette
and
nestcolor::theme_nest
, respectively.color_palette
,
color_palette_core
, h_set_nest_theme
,
s_cox_univariate
.fit_mmrm
,
g_mmrm_diagnostic
, g_mmrm_lsmeans
,
as.rtable.mmrm
, h_mmrm_fixed
,
h_mmrm_cov
, h_mmrm_diagnostic
,
tidy.mmrm
, s_mmrm_lsmeans
,
s_mmrm_lsmeans_single
, summarize_lsmeans
.arm
to study_arm
and
extract
to extract_by_name
.rtables.R
to utils_rtables.R
.cox_regression_inter
into a separate file
from cox_regression
.estimate_incidence_rate.R
to
incidence_rate.R
to match the documentation grouping
name.control_incidence_rate
into a separate file
because it produces a separate documentation file.@md
and removed @order
from
incidence_rate.R
. Modified examples accordingly.prop_schouten
function
documentation.draw_grob
function.h_split_by_subgroups
documentation warning fix for
wrong placing of example block@description
instead of every @descriptionIn
function. Corrected
accordingly summarize_variables_in_cols
g_lineplot
, g_step
,
g_waterfall
, cox_regression
,
score_occurrences
, add_rowcounts
,
odds_ratio
, count_occurrences
,
count_occurrences_by_grade
, explicit_na
,
df_explicit_na
, count_patients_with_event
,
decorate_grob
, combine_groups
,
append_varlabels
, univariate
,
stack_grobs
, count_abnormal
(reference to
abnormal
), count_abnormal_by_baseline
(reference to abnormal_by_baseline
)._pkgdown.yml
polished and tern:::
for tests, examples, and vignettes
when present for the following functions:
h_format_row
,
h_map_for_count_abnormal
make_names
, month2day
,
day2month
empty_vector_if_na
,
aesi_label
, n_available
,
format_xx
, arm
.count_values_funs
, prop_difference
,
combine_counts
.s_count_abnormal
,
a_count_abnormal
.s_count_abnormal_by_baseline
,
a_count_abnormal_by_baseline
,
d_count_abnormal_by_baseline
.s_cox_univariate
function has now deprecated
badge.g_lineplot
with table to automatically scale
the table height and return a ggplot
object.g_ipp
with caption argument and adjust the
position.prop_diff
, tern
function and
related functions to be able to apply a continuity correction in the
Newcombe method.summarize_numeric_in_columns
and
summarize_variables
to allow factor/character summary and
to be able to summarize the number of BLQs
in
AVALC
from ADPC
dataset.sum
option to
summarize_variables
.stream
by
default).h_pkparam_sort
function with argument
key_var
to allow data with different column names.test-table_aet02.R
variant 12.scda
data version to ‘2022-02-28’.pkgdown
site.grDevices
,
stringr
, and viridisLite
.summarize_numeric_in_columns
to
summarize_variables_in_columns
.summarize_vars_numeric_in_cols
to
summarize_vars_in_cols
.g_lineplot
plot were
not connected when missing values.tern.mmrm
.h_pkparam_sort
to order PK PARAM
value based on the order of the dataset generated by
d_pkparam()
.d_pkparam
to generate PK parameter map for
sorting.nudge_y
argument of h_g_ipp
to
be dependent on the data, fixing an issue whereby the baseline labels
were offset incorrectly.stat_mean_ci
and
s_summary.numeric
to calculate the geometric mean with its
confidence intervals.rtables
package refactor.with_label
, var_labels
, and
var_labels<-
to resolve conflict with the
formatters
package, a new dependency.tern
” and “tern
tabulation” vignettes.h_map_for_count_abnormal
to create the map used
in trim_levels_to_map
split function by calling this helper
function. It supports two methods: one with all observed mapping, one
with at least low limit above zero and at least one non missing high
limit.s_summary_numeric_in_cols
and
summarize_vars_numeric_in_cols
functions to generate
summary statistics in columns, mainly used for PK datasets.s_summary.numeric
to use in
s_summary_numeric_in_cols
.tabulate_survival_subgroups
and
tabulate_rsp_subgroups
(Survival Duration and Best Response
analyses) to calculate N
-s based on the records considered
to create the model.estimate_proportion
and related
functions to be able to apply a continuity correction in the Wilson
method.count_abnormal_by_marked
and related
statistics and formatting functions to use a more efficient layout with
.spl_context
argument used for determining denominators and
with trim_levels_to_map
split function under
split_rows_by
to show the desired levels in the table. This
is a breaking change.count_abnormal_by_worst_grade
and related
statistics and formatting functions to use a more efficient layout with
.spl_context
argument used for determining denominators and
with trim_levels_to_map
split function under
split_rows_by
to show the desired levels in the table. This
is a breaking change.count_abnormal
function and related
statistics and formatting functions to use a more efficient layout with
trim_levels_to_map
split function under
split_rows_by
to show the desired levels in the table. Also
updated abnormal
argument to be able to consider more than
one level for each direction. This is a breaking change.estimate_incidence_rate
and
related functions to consider the week as time unit for data input.assertthat
functions that output wrong
data frame names and limited length of failure message outputs.utils.nest
by using the
checkmate
and purrr
packages for validation
and moved get_free_cores
and skip_if_too_deep
functions from utils.nest
into tern
.survival_biomarkers_subgroups
and
response_biomarkers_subgroups
.g_lineplot
plot function, including new
h_format_row
helper function and
control_lineplot_vars
function. Removed
g_summary_by
.h_stack_by_baskets
to
stack events in SMQ and/or CQ basket flag in ADAE data set.s_summary.numeric
.
Added names
attribute to each element of the final list
returned by the s_summary.numeric
function. Added
summary_formats
and summary_labels
helper
functions.df_explicit_na
.h_append_grade_groups
to improve its
flexibility, robustness and clearness, and to make sure the result is
ordering according to the order of grade_groups
. Also,
added remove_single
argument which controls whether the
elements of one-element grade groups are in the output or removed.var_labels
and show_labels
arguments
to count_occurrences
and
count_patients_with_flags
to allow for creation of a title
row.na_level
argument to
count_abnormal_by_baseline
.h_append_grade_groups
to no longer fill-in
empty grade groups with zeros.prop_diff_cmh
to handle edge case of no FALSE (or
TRUE) responses.g_mmrm_diagnostic
to improve error handling
when data is not amenable to the Locally Weighted Scatterplot
Smoothing.g_km
:
arm
variable includes a single level and
annot_coxph = TRUE
.day2month
and month2day
to work with
NA data.stat_mean_ci
and
stat_median_ci
so that they may return different
outputs.h_row_counts
to handle analysis
rows with NULL
cells.LICENCE
and README
with new
package references.error_on_lint: TRUE
to .lintr
.count_abnormal_by_marked
tabulates marked laboratory
abnormalities.summarize_patients_exposure_in_cols
tabulates patient
counts and sum of exposure across all patients.arm
variable.cox_regression
to work without covariates. Also
in case of interaction model summary, p-values for main effect
coefficients are no longer displayed.summarize_vars
now
include quantiles. summarize_vars
now accepts the control
function control_summarize_vars
to specify details about
confidence level for mean and median and quantile details. The
control
argument replaces conf_level
.var_labels
and show_labels
arguments
to count_occurrences_by_grade
.indent
argument in
append_varlabels
to accept non-negative integer to
represent the indent space defined by user. Previous calls with Boolean
indent
will do an integer conversion and produce a
warning.tabulate_survival_subgroups
and related
survival forest plot functions to use total number of events, instead of
observations, as default for scaling the symbol sizes in the plot. (The
user might still use total number of observations manually if they wish
to do so.)h_adsl_adlb_merge_using_worst_flag
will
now impute BTOXGR
for missing visits.count_abnormal_by_worst_grade_by_baseline
and
its related statistic and analysis functions as a simpler design will
create lab abnormality tables.scda
instead of
random.cdisc.data
package.fit_rsp_step
and fit_survival_step
,
the corresponding tidy method tidy.step
as well as the
graph function g_step
.compare_vars
which compares
variables of different types between columns and produces a p-value for
the comparison to the reference column. Function built on top of the
summarize_vars
functionality.cut_quantile_bins
cuts a numeric vector into quantile
bins.fct_collapse_only
collapses levels of a factor and
keeps those in the order provided.fct_explicit_na_if
inserts explicit missings in a
factor based on a condition.range_noinf
is a kind of a wrapper function of
base::range
. It returns c(NA, NA)
instead of
c(-Inf, Inf)
for zero-length data.fit_coxreg_univar
and
fit_coxreg_multivar
is now also possible without treatment
arm. In the univariate case this means that it fits separate univariate
models for the provided covariates and tabulation of corresponding
effect estimates can later occur.fraction
in result returned by
s_count_occurrences
. It contains a list of numerators and
denominators with one element per occurrence.sum_num_patients
and
count_occurrences
for the result unique
and
count_fraction
to return (0, 0) when input is empty.groups_lists
to
extract_survival_subgroups
,
extract_rsp_subgroups
and associated helper functions which
allows to group factor levels of subgroup variables into manually
defined groups, enhancing the flexibility of the resulting forest
graphs.g_forest
now extracts default
arguments from attributes of the input table produced by
tabulate_rsp_subgroups
and
tabulate_survival_subgroups
so that the user does not have
to do this manually anymore.g_km
:
s_surv_time
function to use a newly created
function range_noinf
instead of
base::range
.no_fillin_visits
added to
h_adsl_adlb_merge_using_worst_flag
to specify excluded
visits from the post-baseline worst toxicity grade output. Improved
h_adsl_adlb_merge_using_worst_flag
to include variables
shared between adsl
and adlb
, along with
PARAM
, PARAMCD
, ATOXGR
,
BTOXGR
and optionally AVISIT
,
AVISITN
when by_visit = TRUE
. Prior output
contained USUBJID
, ARMCD
,
PARAMCD
, ATOXGR
, and BTOXGR
.s_surv_timepoint
for cases when there are
zero patients at risk.stat_median_ci
function so that when passing
empty var with empty name, no
row names contain missing values
error would show.s_cox_univariate
function, use
fit_coxreg_univar
function instead.hr
and hr_ci
in
a_coxph_pairwise
and median in s_surv_time
to
align with STREAM.test-table_ttet01.R
and test-table_dort01.R
to
make sure the analysis variable EVNT1
has both levels of
the factor defined.position_surv_med
added to
g_km
to move position of the annotation table with median
survival times.g_km
related to the ignored arguments
pch
and size
which were not passed on to
helper function h_ggkm
.xticks
and max_time
arguments in
g_km
for greater functionality. max_time
added
as an argument in h_xticks
to allow this.prop_diff_cmh
that led to NaN
weighted proportion difference estimates and missing confidence
intervals. Before this change, when including no patients from one
treatment arm for at least one stratum the estimation did not lead to
numeric results.prop_cmh
giving an error in case of at
least one stratum containing less than two observations.n_events
added to
estimate_incidence_rate
.denom
added to
count_occurrences
.yval
and ci_ribbon
added to
g_km
.g_ipp
along
with helpers h_g_ipp
and
h_set_nest_theme
.count_patients_with_events
, now shows zero
counts without percentage.get_mmrm_lsmeans
which did not allow MMRM
analysis of more than 3000 observations.stat_mean_ci
and stat_median_ci
to
handle edge cases with number of elements in input series equal to 1.
For such cases, NA_real_
is now returned, instead of
NA
or +/-Inf
for confidence interval (CI)
estimates.n_lim
argument of stat_mean_ci
to
n_min
to better reflect its desired meaning.This version of tern
introduces a major rewriting of
tern
due to the change to layout based tabulation in
rtables
. tern
now does not build tables
directly anymore, instead it provides analysis functions to build
tables, see the examples. * Counting patients with abnormal values
post-baseline with count_abnormal
. * Counting patients with
graded abnormal values with count_abnormal_by_worst_grade
.
* Counting patients with abnormal values by baseline status with
count_abnormal_by_baseline
. * Counting patients with missed
doses with s_count_missed_doses
and
count_missed_doses
. * Counting patients with event flags
with count_patients_with_event
and
count_patients_with_flags
. * Summarizing variables with
summarize_vars
(supports numeric, factor, character and
logical variables). Note that factors need to have NA
s
converted to na_level
before use. * Summarizing change from
baseline with summarize_change
. * Summarizing variables in
columns with summarize_colvars
. * Estimating difference for
responder proportions with estimate_proportion_diff
. *
Estimating difference for Odds Ratio with
estimate_odds_ratio
. * Testing the difference in responder
proportions with test_proportion_diff
. * Estimating the
responder proportion for the level of a factor with
estimate_multinomial_response
. * Fitting and tabulating the
results of Cox regressions with fit_coxreg_univar
,
fit_coxreg_multivar
and summarize_coxreg
,
respectively. * Pruning occurrence tables (or tables with counts and
fractions) with flexible rules, see ?prune_occurrences
for
details. * Sorting occurrence tables using different options, see
?score_occurrences
for details. * Fitting and tabulating
MMRM models with fit_mmrm
and as.rtable
and
summarize_lsmeans
, see ?tabulate_mmrm
for
details. * Counting the number of unique and non-unique patients with
summarize_num_patients
. * Counting occurrences with
count_occurrences
. * Counting occurrences by grade with
summarize_occurrences_by_grade
and
count_occurrences_by_grade
. * Counting patients and events
in columns with summarize_patients_events_in_cols
. *
Tabulating the binary outcome response by subgroup with
extract_rsp_subgroups
and
tabulate_rsp_subgroups
. * Tabulating the survival duration
by subgroup with extract_survival_subgroups
and
tabulate_survival_subgroups
.
a_mean_sd
, a_median
,
a_n_true_and_freq
, a_count
,
a_q1q3
, a_iqr
, a_range
.s_test_proportion_diff
:
Chi-Squared Test with Schouten Correction.t_contingency
for contingency
tables.splitText
to
dynamicSplitText
to resolve the name conflict with the
package ggpubr
.rreplace_format
for tabulation
post-processing.t_ancova
to create ANCOVA tables,
as well as corresponding elementary table function
t_el_ancova
and summary function
s_ancova
.s_odds_ratio
to estimate Odds
Ratio of response between categories, as well as the corresponding
elementary table function t_el_odds_ratio
.agresti-coull
,
jeffreys
) for s_proportion
.anderson-hauck
and
newcombe
to s_proportion_diff
.s_test_proportion_diff
.t_binary_outcome
takes now lists (instead of character vectors) specified by the helper
function control_binary_comparison
as the arguments
strat_analysis
and unstrat_analysis
. Odds
Ratio estimates and CIs are now removable and included by default,
similarly to the other subsections of the arm comparison analyses. Also
added argument rsp_multinomial
.t_el_multinomial_proportion
.t_abn_shift
.s_mmrm
, as well as
corresponding table functions t_mmrm_lsmeans
,
t_mmrm_cov
, t_mmrm_diagnostic
,
t_mmrm_fixed
, and plot functions
g_mmrm_lsmeans
, g_mmrm_diagnostic
. The results
of these match SAS results (up to numeric precision).a_mmrm
and
t_mmrm
(they give a deprecation warning but still work) to
remove in the next release. The reason is that the results of these
functions don’t match SAS results.g_km
related to numbers in patients at risk
table to correct numbers for integer time-to-event variable inputs.row_by
argument, inputs no longer
require use of nested_by
.stat_mean_ci
and stat_median_ci
for
error bars in ggplot2
.t_coxreg
as single interface for
diverse cox regression types.t_binary_endpoint
and elementary functions:
t_el_proportion
, t_el_proportion_diff
and
t_el_test_proportion_diff
. The supporting summary functions
added are: s_proportion
,
s_adj_proportion_diff
, s_proportion_diff
and
s_test_proportion_diff
.t_events_patyear
to create
event table adjusted person-years.t_abnormality
and the
elementary table function t_el_abnormality
.grade_levels
argument from
t_events_term_grade_id
functions. Post-processing by
reordering the leaves of the table tree creates a different ordering of
rows if required. Creating a helper function will occur at a later
time.prune_zero_rows
argument to
t_events_per_term_grade_id
and
t_max_grade_per_id
to not show rows of all zeros as they
can clutter the visualization in the Shiny app and make it slower.t_summary_by
output when
summarizing numeric columns in parallel with
compare_in_header
.t_coxph
to t_coxph_pairwise
to
reflect the model process, add details in documentation.test.nest
dependency.test.nest
dependency.N
in
t_summary
.t_logistic
for multi-variable logistic
regression table.df_explicit_na
to replace
NA
by explicit values.t_tte
to specify confidence level
independent for survfit
, coxph
, and
ztest
, see the manual.t_rsp
of not showing p-value, odds ratio
and CIs when strata_data
is not NULL
.t_forest_rsp
and
t_forest_tte
, with footnotes in g_forest
.footnotes
, footnotes<-
and
add_footnotes<-
functions to deal with footnotes.conf_int
for confidence interval level
to t_el_forest_rps
, t_forest_rsp
,
t_el_forest_tte
, t_forest_tte
.col_symbol_size
to g_forest
to control the relative size of symbols used in the plot.s_coxph_pairwise
function to perform pairwise
testing, used by t_tte
and t_coxph
.t_count_true
replacing
t_summary_true
.t_count_unique
to create analysis subsets,
added t_el_count_unique
for vectors.t_events_term_id
so that table sort order
is by decreasing frequency instead of alphabetical.color_palette
and a new nest color
palette.utils.nest
.event_type
argument to
t_events_per_term_grade_id
.t_summary_by
.node
S4 class to create trees:
rtables
.keys
and keys<-
functions.tabulate_pairwise
.get_N
, col_N_add_total
,
check_id
.na_as_level
.as_factor_keep_attributes
.r_by
.t_el_disposition
.t_el_forest_tte
, t_el_forest_rsp
.table_tree
argument which returns a
node
object.t_summary.numeric
:
f_numeric
to choose which statistics to
calculate.t_summary.factor
:
denominator
now also allows for omit
if
wanting to omit percentages.t_summary_by
:
by
to row_by
.t_forest_rsp
, t_forest_tte
:
group_data
using
row_by_list
.na_omit_group
.t_count_unique
:
indent
argument, use the indent
function in rtables
. insteadrandom.cdisc.data
to speed up
testing.t_summary.Date
method.save_join
.test.nest
tests:
width_row.names
argument of
g_forest
function into width_row_names
.censor.show
argument of g_km
function into censor_show
.col.legend.title
argument of
g_waterfall
function into
col_legend_title
.na.rm
argument of t_count_unique
function into na_rm
.row.name
argument of
t_count_unique
function into row_name
.na.omit.group
argument of
t_forest_rsp
function into na_omit_group
.na.omit.group
argument of
t_forest_tte
function into na_omit_group
.row.name.TRUE
and row.name.FALSE
arguments of t_summary.logical
into
row_name_true
and row_name_false
respectively.splotTextGrob
into
split_text_grob
.addTable
,
t_summarize_by_visit
,
t_summarize_variables
.t_summary_by
function.g_km
function, renamed kmGrob
into kmCurveGrob
.t_events_*
family of functions.t_summary
and methods for data.frame
,
numeric
, logical
, character
,
factor
, and Date
objects.t_events_per_term_id
,
t_events_per_term_grade_id
: Adverse Events &
Concomitant Treatment Tables.t_max_grade_per_id
, t_count_unique
,
t_events_summary
elementary tables used for the Adverse
Events & Concomitant Treatment Tables.g_waterfall
: Horizontal Waterfall Plot.decorate_grob
, decorate_grob_set
,
decorate_grob_factory
, splitTextGrob
.stack_grobs
, arrange_grobs
,
draw_grob
.t_tte
now shows two rows with ranges for event and
censored times, respectively.g_km
works with one arm survfit
objects.t_summarise_variables
uses now n
instead
of N
as a denominator for calculating percentages for
factors by default.t_rsp
now works when all response values are
TRUE
or FALSE
.t_summarize_variables
as
t_summary
is more powerful.t_summarize_by_visit
with
t_summary_by
will occur in an upcoming release.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.