hespeR

R Handle of The Humanitarian Emergency Settings Perceived Needs Scale (HESPER)

Installation

The development version can be installed from GitHub with:

pak::pak("gnoblet/hespeR")

Overview

hespeR provides tools for handling, cleaning, and analyzing HESPER survey data in R. It includes classes for representing HESPER data, functions for checking and validating datasets, and utilities for common wrangling tasks.

Main Features

• Core Classes:
  • HesperList, HesperListEnhanced, HesperVector for structured data handling.
• Validation Functions:
  • check_missing_vars, check_values_in_set, check_vars_in_set, check_vecs_in_set, check_vector_class, check_dupes
• Options and Variables:
  • hesper_opts, hesper_vars, rec_hesper_opts
• Messages:
  • msg_invalid_values, msg_missing_vars
• Data Utilities:
  • Functions for wrangling and cleaning HESPER data.

Quick Start

library(hespeR)

# Example: Check for missing variables in a data frame
result <- check_missing_vars(df, required_vars = c("hesper_item1", "hesper_item2"))
print(result)

See the vignette for a full workflow example: vignette("hesper_class", package = "hespeR")

Data Resources

Example data and templates are available in the resources/ folder: - hesper_key.xlsx - template_tool_hh.xlsx - template_tool_individual_level.xlsx

Testing and Documentation

• The package includes comprehensive tests (tests/testthat/) and uses roxytypes for type-safe documentation.
• Documentation is available via ?function_name in R.

Roadmap

• ☐ Composition of needed columns
• ☐ Data cleaning
• ☐ Analyses and visualization
• ☐ Publication (reports, presentations)

All steps will include documentation and tests.

Contributing

We welcome contributions! Please see the Minimum Viable Good Practices for High Quality Statistical Software Packages for guidance.