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An Introduction to the Basic Concepts of Food Security







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    Project
    Introduction to Item Response Theory Applied to Food Security Measurement
    Basic Concepts, Parameters and Statistics
    2014
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    The single-parameter logistic item response theory (IRT) measurement model (commonly known as the Rasch model) provides a theoretical base and a set of statistical tools to assess the suitability of a set of survey items for scale construction, create a scale from the items, and compare performance of a scale in various populations and survey contexts. It has been used widely as the statistical basis for survey-based experiential food security measurement. An important step in the validation of food security data is to assess the extent to which the data are consistent with assumptions of the measurement model. In data that meet those assumptions, household raw score (the number of items affirmed by the household) is an ordinal measure of the severity of food insecurity in the household, and the household severity parameter is an interval-level measure of severity. Neither of these important measurement traits is certain if model assumptions are not met. The psychometric validation pro cess is important in initial surveys of language groups and culturally distinct subpopulations and in previously untested modes of survey administration (such as self-administration or on-line administration). Once a set of questions has been assessed in a large sample of a population or subpopulation and found to adequately meet assumptions of the measurement model, psychometric assessment in subsequent surveys may not be necessary. However, psychometric assessment can be valuable in surveys wi th important policy implications to increase confidence in the findings. This paper presents basic concepts and mathematics underlying the Rasch model and describes the model parameters and statistics commonly used to assess food security survey data.
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    Brochure, flyer, fact-sheet
    Linkages between food security, nutrition and social protection: an introduction to basic concepts and principles
    FAO E-learning Academy
    2022
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    This e-learning course explains how social protection programmes can improve food security and nutrition outcomes. It provides learners with the basis needed to understand the work modalities, purpose and usefulness of the Inter-Agency Social Protection Assessment - Food Security and Nutrition (ISPA-FSN) tool presented in the following course of this series: ‘The ISPA-FSN tool: Assessing social assistance programmes for better food security and nutrition.
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    Book (stand-alone)
    Deriving Food Security Information fromNational Household Budget Surveys
    Experiences, Achievements, Challenges
    2008
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    The introductory paper in Part 1 summarizes the efforts and lessons learned from experiences in participating countries to improve food security statistics. Part 2 deals with food security estimates performed at national and sub-national levels in four countries. The papers of Cambodia and the Philippines are examples of food security statistics with gender analysis, while the Lao PDR and Mozambique papers are examples of sub-national analysis. Part 3 addresses measurement approaches of food acquisition and food consumption for the purpose of estimating food security statistics. The examples of Armenia, Cape Verde and Kenya depict detailed effects of how food data are collected on estimates of food security statistics in different settings. Part 4 reviews the policy implications of food security statistics on agriculture in Palestine and food security statistics trends in Moldova. Part 5 shows examples of enhanced analyses using panel data on food consumption in T ajikistan while linking child nutritional status with food security statistics in Georgia. Part 6 proposes methodological approaches for improving food security statistics for policy analysis; the first paper discusses household resilience to food insecurity using Palestinian data, while the last paper describes the linkage between critical food poverty and food deprivation. Finally, Part 7 provides a glossary of selected terminology related to food security statistics.

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