epi_model

Performs clinical trial power calculation, survival analysis, SNP association, logistic regression, k-means clustering, Random Forest, or SVM.

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

epi_model function

<dl><dt>data</dt>
<dd>Input data frame with relevant columns (e.g., outcome, genotypes).</dd>
<dt>formula</dt>
<dd>Model formula (optional, for survival/logistic/rf/svmRadial, e.g., "outcome ~ x").</dd>
<dt>type</dt>
<dd>Model type: "power", "survival", "snp", "logistic", "kmeans", "rf", "svmRadial".</dd>
<dt>...</dt>
<dd>Additional parameters (e.g., n, effect_size for power; k for kmeans).</dd></dl>

Arguments

Unified Epidemiological Modeling — epi_model

<dl>

<dt>data</dt>
<dd>Input data frame with relevant columns (e.g., outcome, genotypes).</dd>


<dt>formula</dt>
<dd>Model formula (optional, for survival/logistic/rf/svmRadial, e.g., "outcome ~ x").</dd>


<dt>type</dt>
<dd>Model type: "power", "survival", "snp", "logistic", "kmeans", "rf", "svmRadial".</dd>


<dt>...</dt>
<dd>Additional parameters (e.g., n, effect_size for power; k for kmeans).</dd>

</dl>

epi_model: Unified Epidemiological Modeling

Description

Usage

Value

Arguments