From 3d950911da18cd0ddcda2162697c40618c98c8a1 Mon Sep 17 00:00:00 2001 From: Ryan O'Dea <70209371+ryan-odea@users.noreply.github.com> Date: Mon, 24 Nov 2025 21:59:15 +0100 Subject: [PATCH] Update README.md --- README.md | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 7e20d3d..8c8fc47 100644 --- a/README.md +++ b/README.md @@ -1,9 +1,10 @@ +[![PyPI version](https://badge.fury.io/py/pySEQTarget.svg)](https://pypi.org/project/pySEQTarget) [![Downloads](https://static.pepy.tech/badge/pySEQTarget)](https://pepy.tech/project/pySEQTarget)[![codecov](https://codecov.io/gh/CausalInference/pySEQTarget/graph/badge.svg?token=DMOVJJUWXP)](https://codecov.io/gh/CausalInference/pySEQTarget)[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)![versions](https://img.shields.io/pypi/pyversions/pySEQTarget.svg) # pySEQTarget - Sequentially Nested Target Trial Emulation Implementation of sequential trial emulation for the analysis of -observational databases. The ‘SEQTaRget’ software accommodates +observational databases. The `SEQTaRget` software accommodates time-varying treatments and confounders, as well as binary and failure -time outcomes. ‘SEQTaRget’ allows to compare both static and dynamic +time outcomes. `SEQTaRget` allows to compare both static and dynamic strategies, can be used to estimate observational analogs of intention-to-treat and per-protocol effects, and can adjust for potential selection bias. @@ -52,5 +53,5 @@ model.collect() # Collection of important information There are several key assumptions in this package - 1. User provided `time_col` begins at 0 per unique `id_col`, we also assume this column contains only integers and continues by 1 for every time step, e.g. (0, 1, 2, 3, 4, ...) is allowed and (0, 1, 2, 2.5, ...) or (0, 1, 4, 5) are not 1. Provided `time_col` entries may be out of order at intake as a sort is enforced at expansion. -2. `eligible_col`, `excused_column_names` and [TODO] are once 1, only 1 (with respect to `time_col`) flag variables. +2. `eligible_col` and elements of `excused_colnames` are once 1, only 1 (with respect to `time_col`) flag variables.