Package: tters 0.1.1

tters: Sequential Target Trial Emulation Data Expansion (Rust + Polars Backend)

Fast, verified data-expansion stage for sequential target trial emulation, backed by a Rust and Polars engine via the 'extendr' crate. Reproduces, bit-for-bit, the expansion output of the 'TrialEmulation' R package. The heavy lifting lives in the 'tte-expand' Rust core crate; this package is a thin binding layer.

Authors:Michael Batech [aut, cre]

tters_0.1.1.tar.gz
tters_0.1.1.zip(r-4.7-x86_64)tters_0.1.1.zip(r-4.7-arm64)tters_0.1.1.zip(r-4.6-x86_64)tters_0.1.1.zip(r-4.6-arm64)tters_0.1.1.zip(r-4.5-x86_64)
tters_0.1.1.tgz(r-4.6-x86_64)tters_0.1.1.tgz(r-4.6-arm64)tters_0.1.1.tgz(r-4.5-x86_64)tters_0.1.1.tgz(r-4.5-arm64)
tters_0.1.1.tar.gz(r-4.7-arm64)tters_0.1.1.tar.gz(r-4.7-x86_64)tters_0.1.1.tar.gz(r-4.6-arm64)tters_0.1.1.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
tters/json (API)

# Install 'tters' in R:

install.packages('tters', repos = c('https://oldschoolcool2.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/oldschoolcool2/rust-tte/issues

On CRAN:

biostatistics causal-inference epidemiology extendr pharmacoepidemiology polars real-world-evidence reproducible-research rust target-trial-emulation cargo

2.70 score 18 exports 2 dependencies

Last updated from:b99deb88b2 (on main). Checks:14 OK, 1 FAIL. Indexed: yes.

Target	Result	Time
linux-devel-arm64	OK	1023
linux-devel-x86_64	OK	1219
source / vignettes	OK	2306
linux-release-arm64	OK	1036
linux-release-x86_64	OK	1260
macos-release-arm64	OK	1635
macos-release-x86_64	OK	3177
macos-oldrel-arm64	OK	1845
macos-oldrel-x86_64	OK	3056
windows-devel-arm64	OK	2089
windows-devel-x86_64	OK	2367
windows-release-arm64	OK	2060
windows-release-x86_64	OK	2308
windows-oldrel-x86_64	OK	1859
wasm-release	FAIL	161

Exports:expand_df expand_parquet expand_trial expand_trial_df expand_trial_weighted expand_trial_weighted_df expand_trial_weighted_fitted expand_trial_weighted_fitted_df expand_trials_tters expand_weighted_df expand_weighted_fitted_df expand_weighted_fitted_parquet expand_weighted_parquet fit_trial_weights fit_trial_weights_df fit_weights_df fit_weights_parquet save_to_tters

Dependencies:bit bit64

Using tters with TrialEmulation

Install | Standalone: expand a cohort in memory | As a TrialEmulation backend

Rendered fromtters.Rmdusingknitr::rmarkdown

Last update: 2026-07-03
Started: 2026-07-03

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Expand an in-memory cohort 'data.frame' into the sequential target-trial layout and return the result as a 'data.frame' — the frame-in/frame-out analogue of 'expand_parquet()', with no intermediate Parquet.	expand_df
Expand a prepared person-time Parquet dataset into the sequential target-trial layout and write the result to 'output_path'.	expand_parquet
Expand a target-trial person-time dataset (ergonomic wrapper)	expand_trial
Expand a target-trial cohort data.frame in memory (ergonomic wrapper)	expand_trial_df
Expand a dataset and attach pre-computed inverse-probability weights	expand_trial_weighted
Expand a cohort data.frame and attach pre-computed weights, in memory (wrapper)	expand_trial_weighted_df
Fit IPW weights and expand a cohort into a weighted trial frame (ergonomic wrapper)	expand_trial_weighted_fitted
Fit IPW weights and expand a cohort data.frame in one call, in memory (wrapper)	expand_trial_weighted_fitted_df
Expand a sequence of target trials with the Rust + Polars engine	expand_trials_tters
Expand an in-memory cohort and attach pre-computed inverse-probability weights, returning the weighted frame as a 'data.frame' — the frame-in/frame-out analogue of 'expand_weighted_parquet()'.	expand_weighted_df
Fit the IPW weights for an in-memory cohort, expand, apply, and return the weighted trial frame as a 'data.frame' — a raw cohort 'data.frame' straight to a weighted, expanded 'data.frame' in one call (no pre-computed factor table, no intermediate Parquet). The frame-in/frame-out analogue of 'expand_weighted_fitted_parquet()'. A 64-bit integer 'id' ('bit64::integer64') round-trips exactly.	expand_weighted_fitted_df
Fit the IPW weights in Rust, expand the cohort, apply the weights, and write the weighted trial frame — a raw cohort to a weighted, expanded frame in one call (no pre-computed factor table).	expand_weighted_fitted_parquet
Expand a person-time Parquet dataset and attach pre-computed inverse-probability weights, writing the weighted frame to 'output_path'.	expand_weighted_parquet
Fit inverse-probability weights for a target-trial cohort (ergonomic wrapper)	fit_trial_weights
Fit inverse-probability weights for a cohort data.frame, in memory (wrapper)	fit_trial_weights_df
Fit the inverse-probability weight factor for an in-memory cohort and return the per-(id, period) factor table (id, period, weight_factor) as a 'data.frame' — the frame-in/frame-out analogue of 'fit_weights_parquet()'.	fit_weights_df
Fit the inverse-probability weight factor for a Parquet cohort in Rust and write the per-(id, period) factor table (id, period, weight_factor).	fit_weights_parquet
Create a 'te_datastore_tters' storage backend	save_to_tters