To generate a basic box plot using ggplot2, enhanced with notcjes and ouliers , and grouped by a categorical variables using an in-built dataset in R

To generate a box plot using ggplot2, enhanced with notches and outliers, and grouped by a categorical variable using an in-built dataset in R.

The create_period_exposures() function provides: Aggregation of exposures into standardized time periods (month, quarter, half-year, year) Support for both point-in-time data and period-based exposure data Special handling for logarithmic values (e.g., decibel-scale noise measurements) Time-weighted averaging to account for varying exposure durations Data quality metrics to assess completeness of exposure information Flexible parameter options to customize the aggregation process

An analysis of NY Cabs in BLR

Easy to read step-by-step introduction to multilevel models

Time-weighted exposure metrics are essential in environmental epidemiology for capturing cumulative or lagged effects of exposures such as noise or air pollution. The calculate_tw_exposure() function provides a flexible way to compute time-weighted averages, minimum/maximum values, and missingness metrics for configurable time windows around each observation.