dtlg0.0.3 package

A Performance-Focused Package for Clinical Trial Tables

AET01_table

Generate Core Safety Tables for Clinical Study Reports

AET02_table

Create AET02-style AE summary table

as_dtlg_table

Convert a TableTree to a dtlg table

calc_counts

Calculate counts of a categorical variable

calc_desc

Calculate descriptive summary statistics for a numeric variable

calc_stats

Calculate summary statistics for a variable

cross_tab_to_obsv_tab

Convert a contingency table to a long-format observation-level data fr...

dt_copy_semantics

Get or set data.table copy semantics

dtlg-package

dtlg: A Performance-Focused Package for Clinical Trial Tables

event_count_by

Summarise adverse events by arm and other grouping variables

event_count

Count events

format_n_pct

Format count(s) and percentage(s) (n (pct%))

indent

Add indentation to strings

label

Retrieve the label of an object

maybe_copy_dt

Return a data.table by reference or by value

merge_table_lists

Merge a list of list-wrapped data.tables into one data.table

multi_event_true

Summarise multiple AESI-like events per treatment arm

nbsp

Generate Non-Breaking Spaces for HTML Output

print_dtlg

Print a dtlg table

round_pct

Rounded percentage

round_sum

Rounds numbers while preserving the total sum

summary_table_by_targets

Create a summary table using multiple rows for grouping on two target ...

summary_table_by

Create a summary table using multiple rows for grouping on one target ...

summary_table

Summary Table

tern_AET01_table

Generate Core Safety Tables (CSR Section 14.3.1) using tern/`rtables...

tern_AET02_table

Generate AET02-style AE summary using tern and rtables

tern_summary_table

Create a clinical reporting table with tern/rtables

total_events

Count total events

with_label

Add a label attribute to an object

Create high-performance clinical reporting tables (TLGs) from ADaM-like inputs. The package provides a consistent, programmatic API to generate common tables such as demographics, adverse event incidence, and laboratory summaries, using 'data.table' for fast aggregation over large populations. Functions support flexible target-variable selection, stratification by treatment, and customizable summary statistics, and return tidy, machine-readable results ready to render with downstream table/formatting packages in analysis pipelines.