Food Insecurity Experience Scale Measurement Training Course

Course overview

Food-security teams need evidence that distinguishes anxiety about food access from reduced dietary quality, smaller portions, skipped meals and whole-day fasting. The Food Insecurity Experience Scale (FIES) provides an internationally recognised experience-based measure for this purpose, but its value depends on disciplined questionnaire adaptation, sampling, data cleaning and Rasch-model analysis. Poorly implemented FIES modules can produce biased prevalence estimates, weak comparability across population groups and reporting that cannot support SDG 2.1.2 or programme decisions.

This five-day course teaches participants to plan, administer, analyse and report FIES data using the FAO methodology. Participants work through the eight FIES questions, reference-period choices, translation and cognitive-testing requirements, survey design, data coding and raw-score checks. They learn how the Rasch model underpins the scale; how to assess item severity, infit and outfit statistics, residual correlations and respondent reliability; and how to estimate moderate or severe food insecurity using the FIES global standard scale. The course also covers weighting, disaggregation, uncertainty intervals and responsible interpretation of results.

Instruction combines worked examples, facilitator demonstrations and practical analysis of a realistic household-survey dataset. Participants use R, Stata and Microsoft Excel to prepare files, run diagnostic checks, calculate prevalence estimates and build tables for management and donor reporting. Each participant leaves with a completed FIES analysis workbook, a reproducible analysis workflow and a short measurement plan for applying the method in their own survey, monitoring system or assessment.

The course is designed for development, humanitarian, government and research professionals who commission, manage or analyse food-security data. It is especially relevant where teams must produce credible population estimates rather than rely only on food-consumption proxies or unstructured perception questions.

Course objectives

By the end of this course, participants will be able to:

• Configure an eight-item FIES survey module with an appropriate respondent, reference period and recall wording
• Adapt FIES questions through translation review and cognitive-testing protocols without changing item meaning
• Build a FIES data-preparation file that codes responses, missing values, weights and survey identifiers correctly
• Calculate FIES raw scores and inspect response patterns for routing, coding and data-quality errors
• Run Rasch-model diagnostics to assess item severity, infit, outfit, residual correlation and reliability
• Estimate moderate-or-severe and severe food-insecurity prevalence using the FIES global standard scale
• Produce disaggregated prevalence tables with confidence intervals for sex, geography and livelihood groups
• Write a defensible FIES results brief that states assumptions, limitations and programme implications

Benefits of attending

Target competencies

Who should attend

• Food Security Analysts — who need to generate and interpret population-level FIES prevalence estimates
• Monitoring, Evaluation, Accountability and Learning Officers — who integrate food-security indicators into survey and results frameworks
• Humanitarian Assessment Officers — who design rapid or multi-sector assessments and need a validated experience-based measure
• National Statistics Office Staff — who produce SDG 2.1.2 reporting or analyse household-survey microdata
• Programme Managers — who need to commission FIES studies and challenge analysis before making resource decisions
• Research Officers — who require a reproducible method for comparing food-insecurity experiences across groups or time periods

Requirements and prerequisites

This is a foundation-to-intermediate course. Participants should be comfortable reading survey questionnaires, working with tabular data and interpreting percentages, sample sizes and basic confidence intervals. Familiarity with food-security concepts such as availability, access, utilisation and stability is helpful, as is prior use of Excel. Participants who intend to run the coding exercises should bring a laptop with Excel and either R or Stata installed. No prior Rasch modelling, psychometrics, advanced statistics or programming experience is required; complete beginners will receive guided templates and step-by-step analysis instructions.

Training methodology

Facilitators introduce each FIES decision point through short technical briefings, then demonstrate it in a worked household-survey file. Participants practise questionnaire review, coding, raw-score inspection and Rasch diagnostics in small groups using R, Stata and Excel templates. Case discussions examine common failures, including altered question meaning, inappropriate reference periods and overinterpretation of subgroup estimates. Daily exercises produce progressively stronger analysis outputs. On the final day, participants complete an application-planning workshop that maps the FIES module, sample, analysis steps and reporting controls required in their own setting.

Course outline

Day 1: FIES foundations and survey design

• Food-security measurement domains and the place of experience-based indicators
• The eight FIES questions and the food-insecurity severity continuum
• Individual versus household respondent selection
• Twelve-month and 30-day reference-period choices
• FIES use for SDG indicator 2.1.2
• Sampling frames, target populations and minimum precision considerations
• Ethical interviewing and referral considerations for sensitive deprivation questions

Workshop: Participants review a draft household questionnaire and produce a corrected FIES module with documented respondent and reference-period decisions.

Day 2: Questionnaire adaptation and data preparation

• FAO FIES wording requirements and prohibited item modifications
• Forward translation, back translation and expert reconciliation
• Cognitive interviewing for food-access experience questions
• Enumerator briefing, probing rules and response recording
• Binary response coding and treatment of don't-know values
• Data dictionaries, variable naming and audit trails
• Raw-score calculation and response-pattern screening

Workshop: Participants clean and document a sample FIES dataset, producing a codebook, raw-score variable and data-quality exception log.

Day 3: Rasch measurement model and diagnostics

• Rasch-model assumptions for FIES item responses
• Item severity parameters and the latent food-insecurity scale
• Respondent ability estimates and score interpretation
• Infit and outfit statistics for item-fit assessment
• Residual correlations and local-dependence checks
• Item characteristic curves and category response patterns
• Reliability, separation and diagnostic reporting thresholds

Workshop: Participants run a Rasch diagnostic workflow on the training dataset and produce an item-fit table with a decision note for each flagged result.

Day 4: Prevalence estimation and comparability

• The FIES global standard scale and cross-country calibration
• Moderate-or-severe and severe food-insecurity thresholds
• Survey weights, stratification and clustered sample designs
• Confidence intervals and coefficient-of-variation checks
• Subgroup disaggregation by sex, age, geography and livelihood
• Small-sample limitations and suppression rules
• Trend analysis and comparability across survey rounds

Workshop: Participants calculate weighted national and subgroup prevalence estimates with confidence intervals and produce a publication-ready results table.

Day 5: Interpretation, reporting and operational application

• Interpreting FIES prevalence alongside food-consumption and market indicators
• Distinguishing descriptive estimates from causal programme effects
• Results narratives for technical, management and donor audiences
• Methods notes covering calibration, diagnostics and limitations
• Data visualisation choices for FIES severity estimates
• Quality-assurance checklist for commissioned FIES surveys
• FIES implementation planning for routine monitoring and evaluations

Workshop: Participants prepare a two-page FIES findings brief and an implementation plan specifying survey, analysis, review and reporting responsibilities.

Tools & standards covered

FAO Food Insecurity Experience Scale Survey Module, R, Stata, Microsoft Excel

A typical training day

Live online deliveries follow the same structure in the East Africa Time zone, with shorter screen blocks and longer breaks.

What the fee includes

How you can take this course

Certification

Participants who complete the full five days receive the Skillset Development Certificate of Completion, stating the course title, course code, dates and delivery format — suitable for professional-development records and employer reimbursement.

Frequently asked questions