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Overview Pages

tern tern-package
tern Package
analyze_functions
Analyze functions
analyze_colvars_functions
Analyze functions in columns
summarize_functions
Summarize functions
formatting_functions stable
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() stable
Control function for descriptive statistics
control_surv_med_annot() control_coxph_annot() stable
Control functions for Kaplan-Meier plot annotation tables
control_coxph() stable
Control function for Cox-PH model
control_coxreg() stable
Control function for Cox regression
control_incidence_rate() stable
Control function for incidence rate
control_lineplot_vars() stable
Control function for g_lineplot()
control_logistic() stable
Control function for logistic regression model fitting
control_riskdiff() stable
Control function for risk difference column
control_step() stable
Control function for subgroup treatment effect pattern (STEP) calculations
control_surv_time() stable
Control function for survfit models for survival time
control_surv_timepoint() stable
Control function for survfit models for patients' survival rate at time points

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() stable
Analyze variables
analyze_vars_in_cols() experimental
Analyze numeric variables in columns
analyze_num_patients() summarize_num_patients() s_num_patients() s_num_patients_content() stable
Count number of patients
analyze_patients_exposure_in_cols() summarize_patients_exposure_in_cols() s_count_patients_sum_exposure() a_count_patients_sum_exposure() stable
Count number of patients and sum exposure across all patients in columns
compare_vars() s_compare() stable
Compare variables between groups
count_abnormal() s_count_abnormal() a_count_abnormal() stable
Count patients with abnormal range values
count_abnormal_by_baseline() s_count_abnormal_by_baseline() a_count_abnormal_by_baseline() stable
Count patients with abnormal analysis range values by baseline status
count_abnormal_by_marked() s_count_abnormal_by_marked() a_count_abnormal_by_marked() stable
Count patients with marked laboratory abnormalities
count_abnormal_by_worst_grade() s_count_abnormal_by_worst_grade() a_count_abnormal_by_worst_grade() stable
Count patients by 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() stable
Count patients with toxicity grades that have worsened from baseline by highest grade post-baseline
count_cumulative() s_count_cumulative() a_count_cumulative() stable
Cumulative counts of numeric variable by thresholds
count_missed_doses() s_count_nonmissing() s_count_missed_doses() a_count_missed_doses() stable
Count number of patients with missed doses by thresholds
count_occurrences() summarize_occurrences() s_count_occurrences() a_count_occurrences() stable
Count occurrences
count_occurrences_by_grade() summarize_occurrences_by_grade() s_count_occurrences_by_grade() a_count_occurrences_by_grade() stable
Count occurrences by grade
summarize_patients_events_in_cols() s_count_patients_and_multiple_events() stable
Count patient events in columns
count_patients_with_event() s_count_patients_with_event() a_count_patients_with_event() stable
Count the number of patients with a particular event
count_patients_with_flags() s_count_patients_with_flags() a_count_patients_with_flags() stable
Count the number of patients with particular flags
count_values() s_count_values() a_count_values() stable
Count specific values
estimate_multinomial_response() s_length_proportion() a_length_proportion() stable
Estimate proportions of each level of a variable
estimate_proportion() s_proportion() a_proportion() stable
Proportion estimation
estimate_incidence_rate() s_incidence_rate() a_incidence_rate() stable
Incidence rate estimation
estimate_odds_ratio() s_odds_ratio() a_odds_ratio() stable
Odds ratio estimation
estimate_proportion_diff() s_proportion_diff() a_proportion_diff() stable
Proportion difference estimation
summarize_coxreg() s_coxreg() a_coxreg() stable
Cox proportional hazards regression
summarize_ancova() s_ancova() a_ancova() stable
Summarize analysis of covariance (ANCOVA) results
summarize_change() s_change_from_baseline() a_change_from_baseline() stable
Summarize change from baseline values or absolute baseline values
summarize_colvars() stable
Summarize variables in columns
summarize_glm_count() s_glm_count() experimental
Summarize Poisson negative binomial regression
summarize_logistic() stable
Multivariate logistic regression table
surv_time() s_surv_time() a_surv_time() stable
Survival time analysis
surv_timepoint() s_surv_timepoint() a_surv_timepoint() s_surv_timepoint_diff() a_surv_timepoint_diff() stable
Survival time point analysis
tabulate_rsp_biomarkers() stable
Tabulate biomarker effects on binary response by subgroup
tabulate_rsp_subgroups() a_response_subgroups() stable
Tabulate binary response by subgroup
tabulate_survival_biomarkers() stable
Tabulate biomarker effects on survival by subgroup
tabulate_survival_subgroups() a_survival_subgroups() stable
Tabulate survival duration by subgroup
test_proportion_diff() s_test_proportion_diff() a_test_proportion_diff() stable
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() stable
Get default statistical methods and their associated formats, labels, and indent modifiers
h_coxreg_inter_effect() h_coxreg_extract_interaction() h_coxreg_inter_estimations() stable
Cox regression helper function for interactions
h_get_format_threshold() h_format_threshold() stable
Format extreme values
h_adlb_abnormal_by_worst_grade() stable
Helper function to prepare ADLB for count_abnormal_by_worst_grade()
h_adlb_worsen() stable
Helper function to prepare ADLB with worst labs
h_adsl_adlb_merge_using_worst_flag() stable
Helper function for deriving analysis datasets for select laboratory tables
h_ancova() stable
Helper function to return results of a linear model
h_append_grade_groups() stable
Helper function for s_count_occurrences_by_grade()
h_count_cumulative() stable
Helper function for s_count_cumulative()
h_coxreg_univar_formulas() h_coxreg_multivar_formula() h_coxreg_univar_extract() h_coxreg_multivar_extract() stable
Helper functions for Cox proportional hazards regression
h_decompose_gg() deprecated
ggplot decomposition
h_format_row() stable
Helper function to format the optional g_lineplot table
h_ggkm() deprecated
Helper function to create a KM plot
h_km_layout() deprecated
Helper function to prepare a 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() stable
Helper functions for multivariate logistic regression
h_map_for_count_abnormal() stable
Helper function to create a map data frame for trim_levels_to_map()
or_glm() or_clogit() stable
Helper functions for odds ratio estimation
h_pkparam_sort() stable
Sort pharmacokinetic data by PARAM variable
h_ppmeans()
Function to return the estimated means using predicted probabilities
prop_diff_wald() prop_diff_ha() prop_diff_nc() prop_diff_cmh() prop_diff_strat_nc() stable
Helper functions to calculate proportion difference
prop_wilson() prop_strat_wilson() prop_clopper_pearson() prop_wald() prop_agresti_coull() prop_jeffreys() stable
Helper functions for calculating proportion confidence intervals
h_rsp_to_logistic_variables() h_logistic_mult_cont_df() h_tab_rsp_one_biomarker() stable
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() stable
Helper functions for tabulating binary response by subgroup
h_split_by_subgroups() stable
Split data frame by subgroups
h_split_param() stable
Split parameters
h_stack_by_baskets() stable
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() stable
Helper functions for subgroup treatment effect pattern (STEP) calculations
h_surv_to_coxreg_variables() h_coxreg_mult_cont_df() h_tab_surv_one_biomarker() stable
Helper functions for tabulating biomarker effects on survival by subgroup
h_survtime_df() h_survtime_subgroups_df() h_coxph_df() h_coxph_subgroups_df() stable
Helper functions for tabulating survival duration by subgroup
h_tab_one_biomarker() stable
Helper function for tabulation of a single biomarker result
h_tbl_coxph_pairwise() stable
Helper function for generating a pairwise Cox-PH table
h_tbl_median_surv() stable
Helper function for survival estimations
h_worsen_counter() stable
Helper function to analyze patients for s_count_abnormal_lab_worsen_by_baseline()
imputation_rule() stable
Apply 1/3 or 1/2 imputation rule to data
labels_use_control() stable
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() stable
Prepare response data estimates for multiple biomarkers in a single data frame
extract_rsp_subgroups() stable
Prepare response data for population subgroups in data frames
extract_survival_biomarkers() stable
Prepare survival data estimates for multiple biomarkers in a single data frame
extract_survival_subgroups() stable
Prepare survival data for population subgroups in data frames
fit_coxreg_univar() fit_coxreg_multivar() stable
Fitting functions for Cox proportional hazards regression
fit_logistic() stable
Fit for logistic regression
fit_rsp_step() stable
Subgroup treatment effect pattern (STEP) fit for binary (response) outcome
fit_survival_step() stable
Subgroup treatment effect pattern (STEP) fit for survival outcome
get_smooths() stable
Smooth function with optional grouping
logistic_regression_cols() stable
Logistic regression multivariate column layout function
logistic_summary_by_flag() stable
Logistic regression summary table
tidy(<glm>) stable
Custom tidy method for binomial GLM results
tidy(<step>) stable
Custom tidy method for STEP results
tidy(<summary.coxph>) tidy(<coxreg.univar>) tidy(<coxreg.multivar>) stable
Custom tidy methods for Cox regression
univariate() stable
Univariate formula special term

Graphs

These function create graphical type output.

s_bland_altman() g_bland_altman() experimental
Bland-Altman analysis
g_forest() stable
Create a forest plot from an rtable
g_ipp() stable
Individual patient plots
g_km() stable
Kaplan-Meier plot
g_lineplot() stable
Line plot with optional table
g_step() stable
Create a STEP graph
g_waterfall() stable
Horizontal waterfall plot

rtables Helper Functions

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

add_riskdiff() stable
Split function to configure risk difference column
add_rowcounts() stable
Layout-creating function to add row total counts
append_varlabels() stable
Add variable labels to top left corner in table
default_na_str() set_default_na_str() stable
Default string replacement for NA values
as.rtable() stable
Convert to rtable
combine_counts()
Combine counts
combine_groups() stable
Reference and treatment group combination
combine_levels() stable
Combine factor levels
combine_vectors()
Element-wise combination of two vectors
h_col_indices() stable
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() stable
Helper functions for accessing information from rtables
rtable2gg() experimental
Convert rtable objects to ggplot objects
split_cols_by_groups() stable
Split columns by groups of levels
to_string_matrix() stable
Convert table into matrix of strings
groups_list_to_df()
Convert list of groups to a data frame
ref_group_position() level_order() stable
Custom split functions

rtables Formatting Functions

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

format_auto() stable
Format automatically using data significant digits
format_count_fraction() stable
Format count and fraction
format_count_fraction_fixed_dp() experimental
Format count and percentage with fixed single decimal place
format_count_fraction_lt10() stable
Format count and fraction with special case for count < 10
format_extreme_values() stable
Format a single extreme value
format_extreme_values_ci() stable
Format extreme values part of a confidence interval
format_fraction() stable
Format fraction and percentage
format_fraction_fixed_dp() stable
Format fraction and percentage with fixed single decimal place
format_fraction_threshold() stable
Format fraction with lower threshold
format_sigfig()
Format numeric values by significant figures
format_xx()
Format XX as a 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() stable
Add titles, footnotes, page Number, and a bounding box to a grid grob
split_text_grob()
Split text according to available text width
decorate_grob_factory()
Update page number
decorate_grob_set() stable
Decorate set of grobs and add page numbering
h_g_ipp() stable
Helper function to create simple line plot over time
h_xticks() stable
Helper function to calculate x-tick positions

Data Helper Functions

These functions are used by other functions to derive data.

aesi_label() stable
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() stable
Combine factor levels
cut_quantile_bins() stable
Cut numeric vector into empirical quantile bins
day2month()
Conversion of days to months
df_explicit_na() stable
Encode categorical missing values in a data frame
d_count_abnormal_by_baseline() stable
Description function for s_count_abnormal_by_baseline()
d_count_cumulative() stable
Description of cumulative count
d_count_missed_doses() stable
Description function that calculates labels for s_count_missed_doses()
d_onco_rsp_label() stable
Description of standard oncology response
d_pkparam() stable
Generate PK reference dataset
d_proportion() stable
Description of the proportion summary
d_proportion_diff() stable
Description of method used for proportion comparison
d_rsp_subgroups_colvars() stable
Labels for column variables in binary response by subgroup table
d_survival_subgroups_colvars() stable
Labels for column variables in survival duration by subgroup table
d_test_proportion_diff() stable
Description of the difference test between two proportions
explicit_na() stable
Missing data
fct_collapse_only() stable
Collapse factor levels and keep only those new group levels
fct_discard() stable
Discard specified levels of a factor
fct_explicit_na_if() stable
Insertion of explicit missing values in a factor
f_conf_level() stable
Utility function to create label for confidence interval
f_pval() stable
Utility function to create label for p-value
h_data_plot() stable
Helper function to tidy survival fit data
month2day() stable
Conversion of months to days
reapply_varlabels()
Reapply variable labels
sas_na() stable
Convert strings to NA
stat_mean_ci() stable
Confidence interval for mean
stat_mean_pval() stable
p-Value of the mean
stat_median_ci() stable
Confidence interval for median
stat_propdiff_ci() stable
Proportion difference and confidence interval
strata_normal_quantile() stable
Helper function for the estimation of stratified quantiles
to_n() stable
Replicate entries of a vector if required
update_weights_strat_wilson() stable
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.

forest_viewport() deprecated
Create a viewport tree for the forest plot
h_decompose_gg() deprecated
ggplot decomposition
h_ggkm() deprecated
Helper function to create a KM plot
h_grob_coxph() deprecated
Helper function to create Cox-PH grobs
h_grob_median_surv() deprecated
Helper function to create survival estimation grobs
h_grob_tbl_at_risk() deprecated
Helper function to create patient-at-risk grobs
h_grob_y_annot() deprecated
Helper function to create grid object with y-axis annotation
h_km_layout() deprecated
Helper function to prepare a KM layout
stack_grobs() deprecated
Stack multiple grobs
arrange_grobs() deprecated
Arrange multiple grobs
draw_grob() deprecated
Draw grob