Quality of anthropometric data in India's National Family Health Survey: Disentangling interviewer and area effect using a cross-classified multilevel model.

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作者： Laxmi Kant,Dwivedi ^[1] ; Kajori,Banerjee ^[2] ; Radhika,Sharma ^[3] ; Rakesh,Mishra ^[4] ; Sowmya,Ramesh ^[5] ; Damodar,Sahu ^[6] ; Sanjay K,Mohanty ^[7] ; K S,James ^[3]

作者单位： Department of Survey Research & Data Analytics, International Institute for Population Sciences, Mumbai, India. ^[1] SVKM's Narsee Monjee Institute of Management Studies (NMIMS), Mumbai, India. ^[2] International Institute for Population Sciences, Mumbai, India. ^[3] UNICEF, New Delhi, India. ^[4] Population Council, New Delhi, India. ^[5] National Institute of Medical Statistics, Indian Council of Medical Research, New Delhi, India. ^[6] Department of Population & Development, International Institute for Population Sciences, Mumbai, India. ^[7]

关键词 Anthropometric measures CCMM, cross-classified multilevel model Children Cross-classified multilevel model Data quality HAZ, height-for-age z-score NFHS, National Family Health Survey NFHS-4 POSHAN, Prime Minister's Overarching Scheme for Holistic Nutrition PSU, Primary Sampling Unit SD, standard deviation SDGs, Sustainable Development Goals Standard deviation Team-level variation WAZ, weight-for-age z-score WHO, World Health Organisation WHZ, weight-for-height z-score Workload of health investigators

DOI 10.1016/j.ssmph.2022.101253

PMID 36268139

发布时间 2022-10-22

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SSM - population health

2022年19卷

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Quality of anthropometric data in India's National Family Health Survey: Disentangling interviewer and area effect using a cross-classified multilevel model.

SSM - population health

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SSM - population health

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Quality of anthropometric data in India's National Family Health Survey: Disentangling interviewer and area effect using a cross-classified multilevel model.

SSM - population health

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SSM - population health

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