Functions

Placeholder

All the functions are below to show they can be pulled from the .rd files, but ideally we’d replace this page with a search.

Function metrics

There are 344 functions exported from the 7 packages in this package family.

Functions present in the packages

package	Exported	Internal
formatters	33	NA
nestcolor	2	NA
rtables	106	NA
teal	22	29
teal.modules.clinical	56	52
teal.modules.general	17	20
tern	108	53

Functions

teal

bookmarkableShinyApp(): Make a Shiny UI function bookmarkable

default_filter(): Refers the default filter state

example_module(): An example list(“teal”) module

get_rcode(): Returns R Code from a teal module

get_rcode_srv(): Server part of get R code module

get_rcode_ui(): Ui part of get R code module

init(): Create the Server and UI Function For the Shiny App

log_app_usage(): Teal Application Usage Logging.

module(): Creates a list(“teal_module”) object.

modules(): Creates a list(“teal_modules”) object.

reporter_previewer_module(): Create a list(“teal”) module for previewing a report

root_modules(): Deprecated: Creates the root modules container

show_rcode_modal(): Show R Code Modal

srv_teal_with_splash(): Server function that loads the data through reactive loading and then delegates

to list(list(“srv_teal()”)) .

ui_teal_with_splash(): UI to show a splash screen in the beginning, then delegate to list(list(“srv_teal()”))

validate_has_data(): Validate that dataset has a minimum number of observations

validate_has_elements(): Validates that vector has length greater than 0

validate_has_variable(): Validates that dataset contains specific variable

validate_in(): Validates that vector includes all expected values

validate_n_levels(): Validate that variables has expected number of levels

validate_no_intersection(): Validates no intersection between two vectors

validate_one_row_per_id(): Validate that dataset has unique rows for key variables

teal.modules.general

add_facet_labels(): Add axis labels that show facetting variable

get_scatterplotmatrix_stats(): Get stats for x-y pairs in scatterplot matrix

tm_a_pca(): Principal component analysis module

tm_a_regression(): Scatterplot and Regression Model

tm_data_table(): Data Table Viewer Teal Module

tm_file_viewer(): File Viewer Teal Module

tm_front_page(): Front page module

tm_g_association(): Stack Plots of variables and show association with reference variable

tm_g_bivariate(): Univariate and bivariate visualizations

tm_g_distribution(): Distribution Module

tm_g_response(): Response Plots

tm_g_scatterplot(): Create a simple scatterplot

tm_g_scatterplotmatrix(): Create a scatterplot matrix

tm_missing_data(): Missing data module

tm_outliers(): Outliers Module

tm_t_crosstable(): Create a simple cross-table

tm_variable_browser(): Variable Browser Teal Module

teal.modules.clinical

add_expr(): Expression List

bracket_expr(): Expressions in Brackets

call_concatenate(): Concatenate expressions via a binary operator

clean_description(): Clean a categorical variable descriptions

color_lab_values(): Mapping function for Laboratory Table

column_annotation_label(): Get full label, useful for annotating plots

cs_to_des_filter(): Convert choices_selected to data_extract_spec with only filter_spec

cs_to_des_select(): Convert choices_selected to data_extract_spec with only select_spec

cs_to_filter_spec(): Convert choices_selected to filter_spec

cs_to_select_spec(): Convert choices_selected to select_spec

extract_input(): Extracts html id for data_extract_ui

get_var_labels(): Get variable labels

h_concat_expr(): Expression Deparsing

is.cs_or_des(): Whether object is of class list(list(“teal.transform::choices_selected()”)) or list(list(“teal.transform::data_extract_spec()”))

pipe_expr(): Expressions as a Pipeline

prepare_arm(): Expression: Arm Preparation

prepare_arm_levels(): Expression: Prepare Arm Levels

split_choices(): Split list(“choices_selected”) objects with interactions into

their component variables

split_col_expr(): Split-Column Expression

split_interactions(): Split interaction terms into their component variables

styled_expr(): Styled Code Printing

tm_a_mmrm(): Teal Module: Teal module for Mixed Model Repeated Measurements (MMRM) analysis

tm_g_barchart_simple(): Simple barchart plot that shows counts per category.

tm_g_ci(): Teal Module: Confidence Interval Plot ( list(“CIG01”) )

tm_g_forest_rsp(): Teal Module: Forest Response Plot teal module

tm_g_forest_tte(): Teal Module: Forest Survival Plot teal Module

tm_g_ipp(): Teal Module: Individual Patient Plot

tm_g_km(): Teal Module: Kaplan-Meier

tm_g_lineplot(): Teal Module: Line Plot

tm_g_pp_adverse_events(): Teal Module: Patient Profile Adverse Events Teal Module

tm_g_pp_patient_timeline(): Teal Module: Patient Profile Timeline Teal Module

tm_g_pp_therapy(): Teal Module: Patient Profile Therapy Teal Module

tm_g_pp_vitals(): Teal Module: Patient Profile Vitals Teal Module

tm_t_abnormality(): Teal Module: Abnormality Summary Table

tm_t_abnormality_by_worst_grade(): Teal Module: Laboratory test results with highest grade post-baseline

tm_t_ancova(): Teal Module: ANCOVA Teal Module

tm_t_binary_outcome(): Teal Module: Binary Outcome Table

tm_t_coxreg(): Teal Module: Cox Regression Model

tm_t_events(): Teal Module: Events by Term

tm_t_events_by_grade(): Teal Module: Events by Grade

tm_t_events_patyear(): Teal module: Event rates adjusted for patient-years

tm_t_events_summary(): Teal Module: Adverse Events Summary

tm_t_exposure(): Teal module: Exposure Table for Risk management plan

tm_t_logistic(): Teal Module: Logistic Regression

tm_t_mult_events(): Teal Module: Multiple Events by Term

tm_t_pp_basic_info(): Teal Module: Patient Profile Basic Info Teal Module

tm_t_pp_laboratory(): Teal Module: Patient Profile Laboratory Teal Module

tm_t_pp_medical_history(): Teal Module: Patient Medical History Teal Module

tm_t_pp_prior_medication(): Teal Module: Patient Prior Medication Teal Module

tm_t_shift_by_arm(): Teal Module: Shift by Arm

tm_t_shift_by_arm_by_worst(): Teal Module: Shift by Arm by Worst

tm_t_shift_by_grade(): Teal Module: Grade Summary Table

tm_t_smq(): Teal Module: list(“SMQ”) Table

tm_t_summary(): Teal Module: Summary of Variables

tm_t_summary_by(): Teal Module: Summarize Variables by Row Groups Module

tm_t_tte(): Teal Module: Time To Event Table Teal Module

tern

add_footnotes<-(): Add Footnotes

add_rowcounts(): Layout Creating Function to Add Row Total Counts

aesi_label(): Labels for Adverse Event Baskets

append_varlabels(): Add Variable Labels to Top Left Corner in Table

as.rtable(): Convert to list(“rtable”)

color_palette(): Deprecated by list(“nestcolor::color_palette”) : Color Palettes Used in NEST

combination_function(): Combination Functions Class

combine_groups(): Reference and Treatment Group Combination

combine_levels(): Combine Factor Levels

compare_variables(): Compare Variables Between Groups

control_coxph(): Control Function for list(“CoxPH”) Model

control_coxreg(): Controls for Cox regression

control_incidence_rate(): Control function for incidence rate

control_lineplot_vars(): Control Function for g_lineplot Function

control_logistic(): Control Function for Logistic Regression Model Fitting

control_step(): Control Function for Subgroup Treatment Effect Pattern (STEP) Calculations

control_summarize_vars(): Control Function for Descriptive Statistics

control_surv_time(): Control Function for list(“survfit”) Model for Survival Time

control_surv_timepoint(): Control Function for list(“survfit”) Model for Patient’s Survival Rate at time point

count_occurrences(): Occurrence Counts

count_occurrences_by_grade(): Occurrence Counts by Grade

count_patients_with_event(): Count the Number of Patients with a Particular Event

count_values_funs(): Counting Specific Values

cox_regression(): Cox Proportional Hazards Regression

cox_regression_inter(): Cox Regression Helper: Interactions

cut_quantile_bins(): Cutting Numeric Vector into Empirical Quantile Bins

d_count_cumulative(): Description of Cumulative Count

d_pkparam(): Generate PK reference dataset

d_proportion(): Description of the Proportion Summary

d_rsp_subgroups_colvars(): Labels for Column Variables in Binary Response by Subgroup Table

d_survival_subgroups_colvars(): Labels for Column Variables in Survival Duration by Subgroup Table

d_test_proportion_diff(): Description of the Difference Test Between Two Proportions

day2month(): Conversion of Days to Months

decorate_grob(): Add Titles, Footnotes, Page Number, and a Bounding Box to a Grid Grob

decorate_grob_set(): Decorate Set of list(“grobs”) and Add Page Numbering

df_explicit_na(): Encode Categorical Missing Values in a Data Frame

draw_grob(): Draw list(“grob”)

estimate_multinomial_rsp(): Estimation of Proportions per Level of Factor

estimate_proportions(): Estimation of Proportions

explicit_na(): Missing Data

extreme_format(): Formatting Extreme Values

f_conf_level(): Utility function to create label for confidence interval

fct_collapse_only(): Collapsing of Factor Levels and Keeping Only Those New Group Levels

fct_discard(): Discard Certain Levels from a Factor

fct_explicit_na_if(): Insertion of Explicit Missings in a Factor

fit_rsp_step(): Subgroup Treatment Effect Pattern (STEP) Fit for Binary (Response) Outcome

fit_survival_step(): Subgroup Treatment Effect Pattern (STEP) Fit for Survival Outcome

footnotes(): Retrieve Footnotes

footnotes<-(): Assign Footnotes

format_count_fraction(): Formatting Count and Fraction

format_fraction(): Formatting Fraction and Percentage

format_fraction_threshold(): Formatting Fraction with Lower Threshold

formatting_functions(): Additional Formatting Functions

g_forest(): Create a Forest Plot based on a Table

g_km(): Kaplan-Meier Plot

g_lineplot(): Line plot with the optional table

g_step(): Create a STEP Graph

g_waterfall(): Horizontal Waterfall Plot

get_smooths(): Smooth Function with Optional Grouping

h_adsl_adlb_merge_using_worst_flag(): Helper Function for Deriving Analysis Datasets for LBT13 and LBT14

h_col_indices(): Obtain Column Indices

h_data_plot(): Helper function: tidy survival fit

h_decompose_gg(): list(“ggplot”) Decomposition

h_format_row(): Helper function to get the right formatting in the optional table in g_lineplot.

h_ggkm(): Helper function: KM plot

h_grob_coxph(): Helper Function: CoxPH Grob

h_grob_median_surv(): Helper Function: Survival Estimation Grob

h_grob_tbl_at_risk(): Helper: Patient-at-Risk Grobs

h_grob_y_annot(): Helper: Grid Object with y-axis Annotation

h_km_layout(): Helper: KM Layout

h_map_for_count_abnormal(): Helper Function to create a map dataframe that can be used in list(“trim_levels_to_map”) split function.

h_pkparam_sort(): Sort list(“PK PARAM”) variable

h_response_biomarkers_subgroups(): Helper Functions for Tabulating Biomarker Effects on Binary Response by Subgroup

h_response_subgroups(): Helper Functions for Tabulating Binary Response by Subgroup

h_split_by_subgroups(): Split Dataframe by Subgroups

h_split_param(): Split parameters

h_stack_by_baskets(): Helper Function to create a new list(“SMQ”) variable in list(“ADAE”) by stacking

list(“SMQ”) and/or list(“CQ”) records.

h_step(): Helper Functions for Subgroup Treatment Effect Pattern (STEP) Calculations

h_survival_biomarkers_subgroups(): Helper Functions for Tabulating Biomarker Effects on Survival by Subgroup

h_survival_duration_subgroups(): Helper Functions for Tabulating Survival Duration by Subgroup

h_tab_one_biomarker(): Helper Function for Tabulation of a Single Biomarker Result

h_tbl_coxph_pairwise(): Helper Function: Pairwise CoxPH table

h_tbl_median_surv(): Helper Function: Survival Estimations

h_xticks(): Helper function: x tick positions

individual_patient_plot(): Individual Patient Plots

kaplan_meier(): Kaplan-Meier Plot

logistic_regression(): Multi-variable logistic regression table

month2day(): Conversion of Months to Days

odds_ratio(): Odds Ratio Estimation

pairwise(): Pairwise formula special term

prop_diff(): Proportion Difference

response_biomarkers_subgroups(): Tabulate Biomarker Effects on Binary Response by Subgroup

s_cox_univariate(): Cox regression including a single covariate - summarized results

sas_na(): Convert Strings to list(“NA”)

score_occurrences(): Occurrence Table Sorting

split_cols_by_groups(): Split Columns by Groups of Levels

stack_grobs(): Stack Multiple Grobs

stat_mean_ci(): Confidence Interval for Mean

stat_median_ci(): Confidence Interval for Median

summarize_colvars(): Summarize Variables in Columns

summarize_num_patients(): Number of patients

summarize_variables(): Summarize Variables

summary_in_cols(): Summary numeric variables in columns

survival_biomarkers_subgroups(): Tabulate Biomarker Effects on Survival by Subgroup

tern-package(): tern Package

to_n(): Replicate Entries of a Vector if Required

to_string_matrix(): Convert Table into Matrix of Strings

univariate(): Univariate formula special term

nestcolor

color_palette(): Color Palettes Used in NEST

theme_nest(): Returns a custom list(“NEST”)

list(“ggplot2”) theme

rtables

AnalyzeVarSplit(): Define a subset tabulation/analysis

CellValue(): Cell Value constructor

ElementaryTable-class(): TableTree classes

EmptyColInfo(): Empty table, column, split objects

InstantiatedColumnInfo-class(): InstantiatedColumnInfo

LabelRow(): Row classes and constructors

ManualSplit(): Manually defined split

MultiVarSplit(): Split between two or more different variables

VarLevelSplit-class(): Split on levels within a variable

VarStaticCutSplit-class(): Splits for cutting by values of a numeric variable

Viewer(): Display an list(list(“rtable”)) object in the Viewer pane in RStudio or in a

browser

[<-,VTableTree,ANY,ANY,list-method(): retrieve and assign elements of a TableTree

add_colcounts(): Add the column population counts to the header

add_existing_table(): Add an already calculated table to the layout

add_overall_col(): Add Overall Column

add_overall_level(): Add an virtual ‘overall’ level to split

all_zero_or_na(): Trimming and Pruning Criteria

analyze(): Generate Rows Analyzing Variables Across Columns

analyze_colvars(): Generate Rows Analyzing Different Variables Across Columns

append_topleft(): Append a description to the ‘top-left’ materials for the layout

as.vector,TableRow-method(): convert to a vector

as_html(): Convert an list(“rtable”) object to a list(“shiny.tag”) html object

basic_table(): Layout with 1 column and zero rows

build_table(): Create a table from a layout and data

cbind_rtables(): cbind two rtables

cell_values(): Retrieve cell values by row and column path

clayout(): Column information/structure accessors

clear_indent_mods(): Clear All Indent Mods from a Table

collect_leaves(): Collect leaves of a table tree

compare_rtables(): Compare two rtables

compat_args(): Compatability Arg Conventions

constr_args(): Constructor Arg Conventions

cont_n_allcols(): Score functions for sorting TableTrees

content_table(): Retrieve or set Content Table from a TableTree

custom_split_funs(): Custom Split Functions

df_to_tt(): Create ElementaryTable from data.frame

do_base_split(): Apply Basic Split (For Use In Custom Split Functions)

export_as_pdf(): Export as PDF

export_as_tsv(): Create Enriched flat value table with paths

export_as_txt(): Export as plain text with page break symbol

format_rcell(): Format rcell

gen_args(): General Argument Conventions

get_formatted_cells(): get formatted cells

head(): Head and tail methods

horizontal_sep(): Access or recursively set header-body separator for tables

in_rows(): Create multiple rows in analysis or summary functions

indent(): Change indentation of all rrows in an rtable

indent_string(): Indent Strings

insert_row_at_path(): Insert Row at Path

insert_rrow(): [DEPRECATED] insert rrows at (before) a specific location

internal_methods(): combine SplitVector objects

is_rtable(): Check if an object is a valid rtable

label_at_path(): Label at Path

length,CellValue-method(): Length of a Cell value

list_wrap_x(): Returns a function that coerces the return values of f to a list

lyt_args(): Layouting Function Arg Conventions

main_title,VTitleFooter-method(): Titles and Footers

make_afun(): Create custom analysis function wrapping existing function

make_row_df(): Column Layout Summary

manual_cols(): Manual column declaration

matrix_form,VTableTree-method(): Transform rtable to a list of matrices which can be used for outputting

names,VTableNodeInfo-method(): Names of a TableTree

no_colinfo(): Exported for use in tern

nrow,VTableTree-method(): Table Dimensions

obj_avar(): Row attribute accessors

obj_name,VNodeInfo-method(): Label, Name and Format accessor generics

pag_tt_indices(): Pagination of a TableTree

path_enriched_df(): Transform TableTree object to Path-Enriched data.frame

prune_table(): Recursively prune a TableTree

rbindl_rtables(): rbind TableTree and related objects

rcell(): Cell value constructors

remove_split_levels(): Split functions

rheader(): Create a header

row_footnotes(): Referential Footnote Accessors

row_paths(): Return List with Table Row/Col Paths

row_paths_summary(): Print Row/Col Paths Summary

rrow(): row

rrowl(): rrowl

rtable(): Create a Table

rtables_aligns(): Currently supported cell value alignments

select_all_levels(): Add Combination Levels to split

sf_args(): Split Function Arg Conventions

simple_analysis(): Default tabulation

sort_at_path(): Sort substructure of a TableTree at a particular Path in the Tree.

spl_context(): .spl_context within analysis and split functions

spl_context_to_disp_path(): Translate spl_context to Path for display in error messages

split_cols_by(): Declaring a column-split based on levels of a variable

split_cols_by_cuts(): Split on static or dynamic cuts of the data

split_cols_by_multivar(): Associate Multiple Variables with Columns

split_rows_by(): Add Rows according to levels of a variable

summarize_row_groups(): Add a content row of summary counts

summarize_rows(): summarize_rows

table_shell(): Table shells

table_structure(): Summarize Table

top_left(): Top Left Material (Experimental)

tostring(): Convert an list(“rtable”) object to a string

tree_children(): Retrieve or set the direct children of a Tree-style object

trim_levels_to_map(): Trim Levels to map

trim_rows(): Trim rows from a populated table without regard for table structure

trim_zero_rows(): Trim Zero Rows

tt_at_path(): Get or set table elements at specified path

tt_to_flextable(): Create a FlexTable object representing an rtables TableTree

update_ref_indexing(): Update footnote indexes on a built table

value_formats(): Value Formats

vars_in_layout(): List Variables required by a pre-data table layout

vpaginate_table(): Deprecated - vertically paginate table

formatters

DM(): DM data

MatrixPrintForm(): Matrix Print Form - Intermediate Representation for ASCII Table Printing

basic_matrix_form(): Create spoof matrix form from a data.frame

basic_pagdf(): Basic/spoof pagination info dataframe

default_hsep(): Default horizontal Separator

divider_height(): Divider Height

ex_adsl(): Simulated CDISC Alike Data for Examples

format_value(): Converts a (possibly compound) value into a string using the list(“format”) information

ifnotlen0(): ‘%||%’ If length-0 alternative operator

is.wholenumber(): is.wholenumber

is_valid_format(): Check if a format is supported

lab_name(): Label, Name and Format accessor generics

list_valid_format_labels(): List with currently support ‘xx’ style format labels grouped by 1d, 2d and 3d

main_title(): General title/footer accessors

make_row_df(): Make row and column layout summary data.frames for use during pagination

matrix_form(): Transform rtable to a list of matrices which can be used for outputting

nlines(): Number of lines required to print a value

padstr(): Pad a string and align within string

pag_indices_inner(): Find Pagination Indices From Pagination Info Dataframe

pagdfrow(): Create row of pagination data frame

print,ANY-method(): Print

propose_column_widths(): Propose Column Widths based on an object’s MatrixPrintForm form

round_fmt(): Round and prepare a value for display

spans_to_viscell(): Transform vectors of spans (with dupblication) to Visibility vector

spread_integer(): spread x into len elements

sprintf_format(): Specify text format via a sprintf format string

toString(): toString

var_labels(): Get Label Attributes of Variables in a list(“data.frame”)

var_labels<-(): Set Label Attributes of All Variables in a list(“data.frame”)

var_labels_remove(): Remove Variable Labels of a list(“data.frame”)

var_relabel(): Copy and Change Variable Labels of a list(“data.frame”)

vert_pag_indices(): Find Column Indicies for Vertical Pagination

with_label(): Return an object with a label attribute

Internal non-exported functions

teal

.log() A logging function

append_module() Function which appends a teal_module onto the children of a teal_modules object

filter_calls_module() Dummy module to show the filter calls generated by the right encoding panel

fold_lines() Fixed line width folding

get_client_timezone() Get Client Timezone

get_datasets_code() Get datasets code

get_dummy_cdisc_data() Get dummy CDISC data

get_dummy_datasets() Get a dummy list(“datasets”) object with list(“ADSL”) data, useful in the examples

get_dummy_filter() Get dummy filter states to apply initially

get_dummy_modules() Get dummy modules

get_rcode_header() Generates header text for analysis items

get_rcode_libraries() Generates library calls from current session info

include_css_files() Include list(“CSS”) files from list(“/inst/css/”) package directory to application header

include_js_files() Include list(“JS”) files from list(“/inst/js/”) package directory to application header

include_teal_css_js() Code to include teal CSS and Javascript files

is_arg_used() Does the object make use of the list(“arg”)

line_pkg_log() Package metadata to add to log file

line_usage_log() app usage data fields to add to log file

modules_depth() Get module depth

pad() Pads a string

reexports() Objects exported from other packages

run_js_files() Run list(“JS”) file from list(“/inst/js/”) package directory

srv_nested_tabs() Server function that returns currently active module

srv_tabs_with_filters() Server function

srv_teal() Server function corresponding to teal

teal-package() teal: Interactive Exploration of Clinical Trials Data

ui_nested_tabs() Create a UI of nested tabs of list(“teal_modules”)

ui_tabs_with_filters() Add right filter panel into each of the top-level list(“teal_modules”) UIs.

ui_teal() Teal app UI

teal.modules.general

call_fun_dots() Call a function with a character vector for the list(“…”) argument

create_sparklines() S3 generic for list(“sparkline”) widget HTML

establish_updating_selection() Creates observers updating the currently selected column

extract_input() Extract html id for data_extract_ui

get_datanames_selected() a tool for ui and server for getting datanames taking into account the datasets_selected vector

get_var_description() Returns a short variable description.

include_css_files() Include list(“CSS”) files from list(“/inst/css/”) package directory to application header

plot_var_summary() Plot variable

remove_outliers_from() Removes the outlier observation from an array

render_single_tab() Renders a single tab in the left-hand side tabset panel

render_tab_header() Renders the text headlining a single tab in the left-hand side tabset panel

render_tab_table() Renders the table for a single dataset in the left-hand side tabset panel

render_tabset_panel_content() Renders the left-hand side list(“tabset”) panel of the module

shared_params() Shared Parameters

teal.modules.general() teal.modules.general: General modules to add to a teal application

validate_input() Validates the variable browser inputs

var_missings_info() Summarizes missings occurrence

var_summary_table() Summarizes variable

variable_type_icons() Get icons to represent variable types in dataset

varname_w_label() Get variable name with label

teal.modules.clinical

arm_ref_comp_observer() Observer for Treatment reference variable

as_num() Parse text input to numeric vector

check_arm_ref_comp() Check if the Treatment variable is reference or compare

control_tte() Control Function for Time-to-Event Teal Module

dyn_assertion() Dynamic assertion

facet_grid_formula() Facetting formula list(“x_facet ~ y_facet”)

get_g_forest_obj_var_name() Utility function for extracting paramcd for forest plots

get_paramcd_label() Extract the associated param value for paramcd

make_barchart_simple_call() list(“ggplot2”) call to generate simple barchart

module_arguments() Standard Module Arguments

substitute_names() Substitute Names in a Quoted Expression

substitute_q() Substitute in Quoted Expressions

teal.modules.clinical() Teal Modules for Standard Clinical Outputs

template_abnormality() Template: Abnormality Summary Table

template_abnormality_by_worst_grade() Template: Laboratory test results with highest grade post-baseline

template_adverse_events() Template: Adverse Events Tab

template_ancova() Template: ANCOVA summary

template_arguments() Standard Template Arguments

template_basic_info() Template: Basic Info

template_binary_outcome() Template: Binary Outcome

template_coxreg_m() Template: Cox Regression Multivariate

template_coxreg_u() Template: Cox Regression Univariate

template_events() Template: Events by Term

template_events_by_grade() Template: Events by Grade

template_events_col_by_grade() Template: Adverse Events grouped by Grade with threshold

template_events_patyear() Template: Event rates adjusted for patient-years

template_events_summary() Template: Adverse Events Summary

template_exposure() Template: Exposure Table for Risk management plan

template_fit_mmrm() Template: Mixed Model Repeated Measurements (MMRM) analysis

template_forest_rsp() Template: Response Forest Plot

template_forest_tte() Template: Survival Forest Plot

template_g_ci() Template: Confidence Interval Plot

template_g_ipp() Template: Individual Patient Plots

template_g_km() Template: Kaplan-Meier

template_g_lineplot() Template: Line Plot

template_laboratory() Template: Laboratory

template_logistic() Template: Logistic Regression

template_medical_history() Template: Medical History

template_mult_events() Template: Events by Term

template_patient_timeline() Template: Patient Timeline Tab

template_prior_medication() Template: Prior Medication

template_shift_by_arm() Template: Shift by Arm

template_shift_by_arm_by_worst() Template: Shift by Arm

template_shift_by_grade() Template: Grade Summary Table

template_smq() Adverse Events Table by Standardized list(“MedDRA”) Query

template_summary() Template: Summary of Variables

template_summary_by() Template: Summarize Variables by Row Groups Module

template_therapy() Template: Therapy

template_tte() Template: Time-to-Event

template_vitals() Template: Vitals

validate_arm() Check if vector is valid as to be used as a treatment arm variable

validate_standard_inputs() Validate standard input values for a teal module

tern

abnormal() Patient Counts with Abnormal Range Values

abnormal_by_baseline() Patient Counts with Abnormal Range Values by Baseline Status

abnormal_by_marked() Count patients with marked laboratory abnormalities

abnormal_by_worst_grade() Patient Counts with the Most Extreme Post-baseline Toxicity Grade per Direction of Abnormality

abnormal_by_worst_grade_worsen() Patient Counts for Laboratory Events (Worsen From Baseline) by Highest Grade Post-Baseline

afun_selected_stats() Get Selected Statistics Names

argument_convention() Standard Arguments

arrange_grobs() Arrange Multiple Grobs

as_factor_keep_attributes() Conversion of a Vector to a Factor

assertions() Additional Assertions for list(“checkmate”)

bins_percent_labels() Labels for Bins in Percent

c_label_n() Content Row Function to Add Row Total to Labels

cfun_by_flag() Constructor for Content Functions given Data Frame with Flag Input

check_diff_prop_ci() Check: Proportion Difference Arguments

check_same_n() Check Element Dimension

combine_counts() Combine Counts

combine_vectors() Combine Two Vectors Element Wise

count_cumulative() Cumulative Counts with Thresholds

count_missed_doses() Counting Missed Doses

count_patients_events_in_cols() Counting Patients and Events in Columns

decorate_grob_factory() Update Page Number

empty_vector_if_na() Return an empty numeric if all elements are list(“NA”) .

estimate_coef() Hazard Ratio Estimation in Interactions

extract_by_name() Extract Elements by Name

forest_viewport() Create a Viewport Tree for the Forest Plot

format_xx() Formatting: XX as Formatting Function

get_covariates() Utility function to return a named list of covariate names.

groups_list_to_df() Convert List of Groups to Data Frame

incidence_rate() Incidence rate

labels_or_names() Labels or Names of List Elements

make_names() Make Names Without Dots

muffled_car_anova() Muffled list(“car::Anova”)

n_available() Number of Available (Non-Missing Entries) in a Vector

prop_diff_test() Difference Test for Two Proportions

prune_occurrences() Occurrence Table Pruning

range_noinf() Re-implemented list(list(“range.default”)) default S3 method for numerical objects only.

It returns list(“c(NA, NA)”) instead of list(“c(-Inf, Inf)”) for zero-length data

without any warnings.

replace_emptys_with_na() Replace all empty string values in data frame

response_subgroups() Tabulate Binary Response by Subgroup

rtables_access() list(“rtables”) Access Helper Functions

s_cox_multivariate() Multivariate Cox Model - summarized results

split_text_grob() Split Text According To Available Text Width

study_arm() Indicate Study Arm Variable in Formula

summarize_ancova() Summary for analysis of covariance (ANCOVA).

summarize_change() Summarize the Change from Baseline or Absolute Baseline Values

summarize_patients_exposure_in_cols() Counting Patients Summing Exposure Across All Patients in Columns

summary_formats() Format Function for Descriptive Statistics

summary_labels() Label Function for Descriptive Statistics

survival_coxph_pairwise() Pairwise CoxPH model

survival_duration_subgroups() Tabulate Survival Duration by Subgroup

survival_time() Survival Time Analysis

survival_timepoint() Survival Time Point Analysis

try_car_anova() list(“tryCatch”) around list(“car::Anova”)

unlist_and_blank_na() Blank for Missing Input