Mouse_df

This dataset, Mouse_df, provides data from mouse cancer trials used in studies
by Royston and Altman. The dataset includes 181 observations and 4 variables,
covering information on treatment assignment, survival time, outcome, and mouse
identifiers. Some observations contain missing values.

Provides a comprehensive set of datasets and tools for 'causal inference' research.
The package includes data from clinical trials, cancer studies, epidemiological surveys, environmental exposures, and health-related observational studies.
Designed to facilitate causal analysis, risk assessment, and advanced statistical modeling,
it leverages datasets from packages such as 'causalOT', 'survival', 'causalPAF', 'evident', 'melt', and 'sanon'.
The package is inspired by the foundational work of Pearl (2009) <doi:10.1017/CBO9780511803161> on causal inference frameworks.

Tomás Valderrama

ForCausality

A Curated Collection of 'Causal Inference' Datasets and Tools

Mouse_df function

A data frame with 181 observations and 4 variables:<dl>
 <dt>trt</dt>
<dd>Treatment group (factor)</dd> <dt>days</dt>
<dd>Survival time in days (numeric)</dd> <dt>outcome</dt>
<dd>Trial outcome (factor)</dd> <dt>id</dt>
<dd>Mouse identifier (integer)</dd>
</dl>

Format

Mouse Cancer Trial Data — Mouse_df

A data frame with 181 observations and 4 variables:<dl>
 <dt>trt</dt>
<dd>Treatment group (factor)</dd>

 <dt>days</dt>
<dd>Survival time in days (numeric)</dd>

 <dt>outcome</dt>
<dd>Trial outcome (factor)</dd>

 <dt>id</dt>
<dd>Mouse identifier (integer)</dd>


</dl>

Mouse_df: Mouse Cancer Trial Data

Description

Usage

Arguments

Format

Details