Voices of the Hungry

Analyse the Data

Resources for analyzing the data

Together, the FIES items compose a scale designed to cover a range of severity of food insecurity and should be analyzed together as a scale; results should not be reported in terms of percent of positive responses to individual questions.  This is because the items are meant to collectively scan a broad range of severity of food insecurity. Taken together, every item contributes information to measuring food insecurity along the severity continuum, increases precision, and reduces the overall impact of measurement error.  

FIES data are analysed by applying the Rasch model, which is widely used in health, education and psychology studies and provides the statistical basis for experience-based food security measurement.  While other experience-based food security scales have used the raw score (sum of affirmative responses) to classify respondents by the severity of their food insecurity, the resulting prevalence rates are not directly comparable. The methods developed by FAO for the analysis of FIES data, however, are designed to produce measures of food insecurity that are comparable across countries.

The materials included here have been developed by FAO to facilitate the use of the FIES.



Analytical tools

RM.weights: Software for FIES data analysis

As the official statistical software of the FAO Voices of the Hungry (VoH) project, R is used for the implementation of methods to estimate food insecurity prevalence. This zip folder contains the R software package and explanatory documents to carry out statistical validation of the data and to calculate the prevalence of food insecurity.

FIES Excel template

This Excel template is provided to facilitate the equating process to produce comparable estimates of the prevalence of food insecurity. Detailed instructions are provided in Lesson 4 of the FIES e-learning course.

Report Writing

Report texmplate

This report template is intended to guide users of the FIES in writing a comprehensive report covering the application of the FIES and interpretation of results.