survival_data

A dataset containing simulated data for survival analysis in epidemiological studies.

datasets

Integrates methods for epidemiological analysis, modeling, and visualization, including functions for summary statistics, SIR (Susceptible-Infectious-Recovered) modeling, DALY (Disability-Adjusted Life Years) estimation, age standardization, diagnostic test evaluation, NLP (Natural Language Processing) keyword extraction, clinical trial power analysis, survival analysis, SNP (Single Nucleotide Polymorphism) association, and machine learning methods such as logistic regression, k-means clustering, Random Forest, and Support Vector Machine (SVM). Includes datasets for prevalence estimation, SIR modeling, genomic analysis, clinical trials, DALY, diagnostic tests, and survival analysis. Methods are based on Gelman et al. (2013) <doi:10.1201/b16018> and Wickham et al. (2019, ISBN:9781492052040>.

Esther Atsabina Wanjala

EpidigiR

Digital Epidemiological Analysis and Visualization Tools

survival_data function

A data frame with 100 rows and 3 columns:<dl>
 <dt>id</dt>
<dd>Character, unique identifier for each individual.</dd> <dt>time</dt>
<dd>Numeric, time to event (e.g., years until death or censoring).</dd> <dt>status</dt>
<dd>Numeric, event status (0 = censored, 1 = event occurred).</dd>
</dl>

Format

Survival Analysis Data — survival_data

A data frame with 100 rows and 3 columns:<dl>
 <dt>id</dt>
<dd>Character, unique identifier for each individual.</dd>

 <dt>time</dt>
<dd>Numeric, time to event (e.g., years until death or censoring).</dd>

 <dt>status</dt>
<dd>Numeric, event status (0 = censored, 1 = event occurred).</dd>


</dl>

survival_data: Survival Analysis Data

Description

Usage

Arguments

Format

Examples