survey_data

A dataset containing simulated survey data for age standardization 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

survey_data function

A data frame with 20 rows and 3 columns:<dl>
 <dt>age_group</dt>
<dd>Character, age group (e.g., 0-19, 20-39, 40-59, 60+).</dd> <dt>rates</dt>
<dd>Numeric, disease rates (e.g., cases per 1000).</dd> <dt>pop_weights</dt>
<dd>Numeric, population weights for standardization.</dd>
</dl>

Format

Survey Data for Age Standardization — survey_data

A data frame with 20 rows and 3 columns:<dl>
 <dt>age_group</dt>
<dd>Character, age group (e.g., 0-19, 20-39, 40-59, 60+).</dd>

 <dt>rates</dt>
<dd>Numeric, disease rates (e.g., cases per 1000).</dd>

 <dt>pop_weights</dt>
<dd>Numeric, population weights for standardization.</dd>


</dl>

survey_data: Survey Data for Age Standardization

Description

Usage

Arguments

Format

Examples