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Overview Pages

tern tern-package
tern Package
analyze_functions
Analyze Functions
analyze_colvars_functions
Analyze Functions on Columns
summarize_functions
Summarize Functions
formatting_functions
Formatting Functions

Control Functions

These functions capture options in lists and take care of defaults (and checks where applicable). They avoid cluttering of function signatures with long lists of single arguments.

control_analyze_vars()
Control Function for Descriptive Statistics
control_coxph()
Control Function for 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_surv_time()
Control Function for survfit Model for Survival Time
control_surv_timepoint()
Control Function for survfit Model for Patient's Survival Rate at time point

Analysis Functions

Analyze functions with their corresponding statistics functions and formatted analysis functions.

  • Analyze functions are used in combination with rtables layout functions in the pipeline which creates the table.

  • Statistics functions (denoted by s_ prefix) compute the numbers that are tabulated later. In order to separate computation from formatting, they do not take care of rcell type formatting themselves.

  • Formatted analysis functions (denoted by a_ prefix) have the same arguments as the corresponding statistics functions, and can be further customized by calling rtables::make_afun() on them. They are used as afun in rtables::analyze().

analyze_vars() s_summary() a_summary() summarize_vars()
Analyze Variables
analyze_vars_in_cols()
Summary numeric variables in columns
analyze_num_patients() summarize_num_patients() s_num_patients() s_num_patients_content()
Number of Patients
analyze_patients_exposure_in_cols() summarize_patients_exposure_in_cols() s_count_patients_sum_exposure() a_count_patients_sum_exposure()
Counting Patients Summing Exposure Across All Patients in Columns
compare_vars() s_compare() a_compare()
Compare Variables Between Groups
count_abnormal() s_count_abnormal() a_count_abnormal()
Patient Counts with Abnormal Range Values
count_abnormal_by_baseline() s_count_abnormal_by_baseline() a_count_abnormal_by_baseline()
Patient Counts with Abnormal Range Values by Baseline Status
count_abnormal_by_marked() s_count_abnormal_by_marked() a_count_abnormal_by_marked()
Count Patients with Marked Laboratory Abnormalities
count_abnormal_by_worst_grade() s_count_abnormal_by_worst_grade() a_count_abnormal_by_worst_grade()
Patient Counts with the Most Extreme Post-baseline Toxicity Grade per Direction of Abnormality
count_abnormal_lab_worsen_by_baseline() s_count_abnormal_lab_worsen_by_baseline() a_count_abnormal_lab_worsen_by_baseline()
Patient Counts for Laboratory Events (Worsen From Baseline) by Highest Grade Post-Baseline
count_cumulative() s_count_cumulative() a_count_cumulative()
Cumulative Counts with Thresholds
count_missed_doses() s_count_nonmissing() s_count_missed_doses() a_count_missed_doses()
Counting Missed Doses
count_occurrences() summarize_occurrences() s_count_occurrences() a_count_occurrences()
Occurrence Counts
count_occurrences_by_grade() summarize_occurrences_by_grade() s_count_occurrences_by_grade() a_count_occurrences_by_grade()
Occurrence Counts by Grade
summarize_patients_events_in_cols() s_count_patients_and_multiple_events()
Counting Patients and Events in Columns
count_patients_with_event() s_count_patients_with_event() a_count_patients_with_event()
Count the Number of Patients with a Particular Event
count_patients_with_flags() s_count_patients_with_flags() a_count_patients_with_flags()
Count the Number of Patients with Particular Flags
count_values() s_count_values() a_count_values()
Counting Specific Values
estimate_multinomial_response() s_length_proportion() a_length_proportion()
Estimation of Proportions per Level of Factor
estimate_proportion() s_proportion() a_proportion()
Estimation of Proportions
estimate_incidence_rate() s_incidence_rate() a_incidence_rate()
Incidence Rate
estimate_odds_ratio() s_odds_ratio() a_odds_ratio()
Odds Ratio Estimation
estimate_proportion_diff() s_proportion_diff() a_proportion_diff()
Proportion Difference
summarize_coxreg() s_coxreg() a_coxreg()
Cox Proportional Hazards Regression
summarize_ancova() s_ancova() a_ancova()
Summary for analysis of covariance (ANCOVA).
summarize_change() s_change_from_baseline() a_change_from_baseline()
Summarize the Change from Baseline or Absolute Baseline Values
summarize_colvars()
Summarize Variables in Columns
summarize_glm_count() s_glm_count() a_glm_count()
Summary for Poisson Negative Binomial.
summarize_logistic()
Multivariate Logistic Regression Table
surv_time() s_surv_time() a_surv_time()
Survival Time Analysis
surv_timepoint() s_surv_timepoint() a_surv_timepoint() s_surv_timepoint_diff() a_surv_timepoint_diff()
Survival Time Point Analysis
tabulate_rsp_biomarkers()
Tabulate Biomarker Effects on Binary Response by Subgroup
tabulate_rsp_subgroups() a_response_subgroups()
Tabulate Binary Response by Subgroup
tabulate_survival_biomarkers()
Tabulate Biomarker Effects on Survival by Subgroup
tabulate_survival_subgroups() a_survival_subgroups()
Tabulate Survival Duration by Subgroup
test_proportion_diff() s_test_proportion_diff() a_test_proportion_diff()
Difference Test for Two Proportions

Analysis Helper Functions

These functions are useful in defining an analysis.

get_stats() get_formats_from_stats() get_labels_from_stats() get_indents_from_stats() tern_default_stats tern_default_formats tern_default_labels summary_formats() summary_labels() summary_custom()
Get default statistical methods and their associated formats, labels, and indent modifiers
h_coxreg_inter_effect() h_coxreg_extract_interaction() h_coxreg_inter_estimations()
Cox Regression Helper: Interactions
h_get_format_threshold() h_format_threshold()
Formatting Extreme Values
h_adlb_abnormal_by_worst_grade()
Helper function to prepare ADLB for count_abnormal_by_worst_grade()
h_adlb_worsen()
Helper Function to Prepare ADLB with Worst Labs
h_adsl_adlb_merge_using_worst_flag()
Helper Function for Deriving Analysis Datasets for LBT13 and LBT14
h_ancova()
Helper Function to Return Results of a Linear Model
h_append_grade_groups()
Helper function for s_count_occurrences_by_grade()
h_count_cumulative()
Helper Function for s_count_cumulative()
h_coxreg_univar_formulas() h_coxreg_multivar_formula() h_coxreg_univar_extract() h_coxreg_multivar_extract()
Helper Functions for Cox Proportional Hazards Regression
h_decompose_gg()
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_km_layout()
Helper: KM Layout
h_get_interaction_vars() h_interaction_coef_name() h_or_cat_interaction() h_or_cont_interaction() h_or_interaction() h_simple_term_labels() h_interaction_term_labels() h_glm_simple_term_extract() h_glm_interaction_extract() h_glm_inter_term_extract() h_logistic_simple_terms() h_logistic_inter_terms()
Helper Functions for Multivariate Logistic Regression
h_map_for_count_abnormal()
Helper Function to create a map dataframe that can be used in trim_levels_to_map split function.
or_glm() or_clogit()
Helper Functions for Odds Ratio Estimation
h_pkparam_sort()
Sort Data by PK PARAM Variable
prop_diff_wald() prop_diff_ha() prop_diff_nc() prop_diff_cmh() prop_diff_strat_nc()
Helper Functions to Calculate Proportion Difference
prop_wilson() prop_strat_wilson() prop_clopper_pearson() prop_wald() prop_agresti_coull() prop_jeffreys()
Helper Functions for Calculating Proportion Confidence Intervals
h_rsp_to_logistic_variables() h_logistic_mult_cont_df() h_tab_rsp_one_biomarker()
Helper Functions for Tabulating Biomarker Effects on Binary Response by Subgroup
h_proportion_df() h_proportion_subgroups_df() h_odds_ratio_df() h_odds_ratio_subgroups_df()
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 SMQ variable in ADAE by stacking SMQ and/or CQ records.
h_step_window() h_step_trt_effect() h_step_survival_formula() h_step_survival_est() h_step_rsp_formula() h_step_rsp_est()
Helper Functions for Subgroup Treatment Effect Pattern (STEP) Calculations
h_surv_to_coxreg_variables() h_coxreg_mult_cont_df() h_tab_surv_one_biomarker()
Helper Functions for Tabulating Biomarker Effects on Survival by Subgroup
h_survtime_df() h_survtime_subgroups_df() h_coxph_df() h_coxph_subgroups_df()
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_worsen_counter()
Helper Function to Analyze Patients for s_count_abnormal_lab_worsen_by_baseline()
imputation_rule()
Apply 1/3 or 1/2 Imputation Rule to Data
labels_use_control()
Update Labels According to Control Specifications

Model-Specific Functions

These functions help with fitting or extracting results from specific models.

estimate_coef()
Hazard Ratio Estimation in Interactions
extract_rsp_biomarkers()
Prepares Response Data Estimates for Multiple Biomarkers in a Single Data Frame
extract_rsp_subgroups()
Prepares Response Data for Population Subgroups in Data Frames
extract_survival_biomarkers()
Prepares Survival Data Estimates for Multiple Biomarkers in a Single Data Frame
extract_survival_subgroups()
Prepares Survival Data for Population Subgroups in Data Frames
fit_coxreg_univar() fit_coxreg_multivar()
Fits for Cox Proportional Hazards Regression
fit_logistic()
Fit for Logistic Regression
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
get_smooths()
Smooth Function with Optional Grouping
logistic_regression_cols()
Logistic Regression Multivariate Column Layout Function
logistic_summary_by_flag()
Logistic Regression Summary Table Constructor Function
tidy(<glm>)
Custom Tidy Method for Binomial GLM Results
tidy(<step>)
Custom Tidy Method for STEP Results
tidy(<summary.coxph>) tidy(<coxreg.univar>) tidy(<coxreg.multivar>)
Custom Tidy Methods for Cox Regression
univariate()
Univariate Formula Special Term

Graphs

These function create graphical type output.

s_bland_altman() g_bland_altman()
Bland Altman analysis
g_forest()
Create a forest plot from an rtable
g_km()
Kaplan-Meier Plot
g_lineplot()
Line plot with the optional table
g_step()
Create a STEP Graph
g_waterfall()
Horizontal Waterfall Plot
g_ipp()
Individual Patient Plots

rtables Helper Functions

These functions help to work with the rtables package and may be moved there later.

add_riskdiff()
Split Function to Configure Risk Difference Column
add_rowcounts()
Layout Creating Function to Add Row Total Counts
append_varlabels()
Add Variable Labels to Top Left Corner in Table
default_na_str() set_default_na_str()
Default string replacement for NA values
as.rtable()
Convert to rtable
combine_counts()
Combine Counts
combine_groups()
Reference and Treatment Group Combination
combine_levels()
Combine Factor Levels
combine_vectors()
Combine Two Vectors Element Wise
h_col_indices()
Obtain Column Indices
h_row_first_values() h_row_counts() h_row_fractions() h_col_counts() h_content_first_row() is_leaf_table() check_names_indices()
rtables Access Helper Functions
rtable2gg()
Convert rtable object to ggplot object
split_cols_by_groups()
Split Columns by Groups of Levels
to_string_matrix()
Convert Table into Matrix of Strings
groups_list_to_df()
Convert List of Groups to Data Frame
ref_group_position() level_order()
Custom Split Functions

rtables Formatting Functions

These functions provide customized formatting rules to work with the rtables package.

format_auto()
Automatic formats from data significant digits
format_count_fraction()
Formatting Count and Fraction
format_count_fraction_fixed_dp()
Formatting Count and Percentage with Fixed Single Decimal Place
format_count_fraction_lt10()
Formatting Count and Fraction with Special Case for Count < 10
format_extreme_values()
Formatting a Single Extreme Value
format_extreme_values_ci()
Formatting Extreme Values Part of a Confidence Interval
format_fraction()
Formatting Fraction and Percentage
format_fraction_fixed_dp()
Formatting Fraction and Percentage with Fixed Single Decimal Place
format_fraction_threshold()
Formatting Fraction with Lower Threshold
format_sigfig()
Formatting Numeric Values By Significant Figures
format_xx()
Formatting: XX as Formatting Function

rtables Scoring Functions

These functions can help with table sorting.

rtables Pruning Functions

These functions and classes help with flexible pruning of tables.

Graph Helper Functions

These functions are useful to modify graphs.

decorate_grob()
Add Titles, Footnotes, Page Number, and a Bounding Box to a Grid Grob
decorate_grob_set()
Decorate Set of grobs and Add Page Numbering
h_g_ipp()
Helper Function To Create Simple Line Plot over Time
arrange_grobs()
Arrange Multiple Grobs
draw_grob()
Draw grob
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
stack_grobs()
Stack Multiple Grobs
h_xticks()
Helper function: x tick positions
forest_viewport()
Create a Viewport Tree for the Forest Plot

Data Helper Functions

These functions are used by other functions to derive data.

aesi_label()
Labels for Adverse Event Baskets
as_factor_keep_attributes()
Conversion of a Vector to a Factor
bins_percent_labels()
Labels for Bins in Percent
combine_levels()
Combine Factor Levels
cut_quantile_bins()
Cutting Numeric Vector into Empirical Quantile Bins
day2month()
Conversion of Days to Months
df_explicit_na()
Encode Categorical Missing Values in a Data Frame
d_count_abnormal_by_baseline()
Description Function for s_count_abnormal_by_baseline()
d_count_cumulative()
Description of Cumulative Count
d_count_missed_doses()
Description Function that Calculates Labels for s_count_missed_doses().
d_onco_rsp_label()
Description of Standard Oncology Response
d_pkparam()
Generate PK reference dataset
d_proportion()
Description of the Proportion Summary
d_proportion_diff()
Description of Method Used for Proportion Comparison
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
explicit_na()
Missing Data
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
f_conf_level()
Utility function to create label for confidence interval
f_pval()
Utility function to create label for p-value
h_data_plot()
Helper function: tidy survival fit
month2day()
Conversion of Months to Days
reapply_varlabels()
Reapply Variable Labels
sas_na()
Convert Strings to NA
stat_mean_ci()
Confidence Interval for Mean
stat_mean_pval()
p-Value of the Mean
stat_median_ci()
Confidence Interval for Median
stat_propdiff_ci()
Proportion Difference and Confidence Interval
strata_normal_quantile()
Helper Function for the Estimation of Stratified Quantiles
to_n()
Replicate Entries of a Vector if Required
update_weights_strat_wilson()
Helper Function for the Estimation of Weights for prop_strat_wilson

Assertion Functions

These functions supplement those in the checkmate package.

Data

Data included in the package.

Deprecated Functions

Functions that are currently deprecated within tern.