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ProjectIntroduction to Item Response Theory Applied to Food Security Measurement
Basic Concepts, Parameters and Statistics
2014Also available in:
No results found.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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