ShinyDataMatcher: A user-friendly application for integrating survey data - Lucia Guastadisegni; Fedele Greco; Carlo Trivisano (PLoS ONE, 2026)
In this work, we introduce ShinyDataMatcher , a user-friendly R Shiny application designed to support the integration of survey data through statistical matching. The tool enables practitioners to import, explore and process survey data, harmonize variables, select appropriate matching variables, and apply a wide range of macro- and micro-level matching methods without writing any code. The application guides the user through the full workflow of a matching exercise, from data preparation to the creation of a synthetic matched dataset, and includes diagnostic tools for assessing matching quality. To illustrate its capabilities, we present an application based on the Italian Household Budget Survey (HBS) and the Survey on Household Income and Wealth (SHIW), where the goal is to fuse income and expenditure information and to construct a Social Accounting Matrix (SAM). The example also highlights how repeated random hot-deck imputations can be used to account for the additional uncertainty induced by statistical matching. Overall, ShinyDataMatcher provides a transparent and accessible environment for exploring, prototyping, and implementing statistical matching procedures, lowering the technical barriers that often limit their use in applied and official-statistics contexts.