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September 29, 2025American Journal of Theoretical and Applied StatisticsOpen Access

Application of Newton Raphson, Fisher’s Scoring, and Reweighted Least Squares Methods for Multinomial Regression in Investigating Childhood Malnutrition in Kenya

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Authors

PKPriscilla W. KariukiJKJames Kahiri

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Overview

This analysis investigates childhood malnutrition outcomes in Kenya using multinomial regression methods, revealing significant factors affecting malnutrition.

Key Points

  • The study identifies key demographic and socioeconomic factors affecting childhood malnutrition outcomes in Kenya.
  • Using the 2022 Kenya Demographic and Health Survey data, the study evaluates three estimation methods for accuracy.
  • Iterative parameter estimation approaches demonstrated varying classification accuracy and computational efficiency for multinomial regression.
  • The findings aim to inform public health interventions by revealing causal relationships pertinent to malnutrition in high-risk children.

Cite This Study

Kariuki et al. (2025) studied this question.

synapsesocial.com/papers/68da58e0c1728099cfd11735https://doi.org/10.11648/j.ajtas.20251405.11
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