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- W4200344822 abstract "This chapter introduces discriminant analysis as a tool to identify the most important determinant of food security and nutritional status that can predict best among a large pool of such independent variables. Such variables need to be identified for context- and community-specific food and nutrition interventions. We present a case study from the United States, which links economic conditions and participation in Nutrition Assistance Programs. We also present the impact of climate change on nutrition in Ethiopia and Asia. This chapter reviews selected case studies that attempt to identify good predictors of food insecurity, poverty, and malnutrition. Various steps of discriminant analysis, such as specifying the dependent and predictor variables, determining the method of selection criteria for entering the predictor variables in the modes and tests of a priori assumptions of the model, interpretation of discriminant functions and validation of results are described with examples. STATA and R codes are given for learning analytical techniques of this chapter." @default.
- W4200344822 created "2021-12-31" @default.
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- W4200344822 date "2022-01-01" @default.
- W4200344822 modified "2023-09-25" @default.
- W4200344822 title "Predicting child nutritional status using related socioeconomic variables—application of discriminant function analysis" @default.
- W4200344822 doi "https://doi.org/10.1016/b978-0-12-820477-1.00001-2" @default.
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