Biostatistics Methods in Nutritional Research
A special issue of Nutrients (ISSN 2072-6643). This special issue belongs to the section "Nutrition Methodology & Assessment".
Deadline for manuscript submissions: 15 May 2025 | Viewed by 2298
Special Issue Editors
Interests: data analysis in nutritional research and food sciences; data science; statistical methods in bioinformatics; epidemiology; spatial statistics
Interests: biostatistics; data analysis; epidemiology; environmental epidemiology; data science
Special Issue Information
Dear Colleagues,
Biostatistical data analysis and data science are widely used in nutritional research and food sciences. They are remarkably relevant in identifying the role of key factors in predictive analysis (e.g. explainable machine learning and deep learning), statistical modelling (e.g., generalized linear mixed modelling, generalized estimating equations, survival analysis) and causal inference, (e.g., mediators, moderator, confounders, colliders, propensity score). Nevertheless, study design, sampling methods and questionnaire validation also assume a very important role in this research field.
Over the last few years, nutritional research and food sciences have involved a number of study where black-box and statistical methods and causal approaches have been used to produce scientific evidence. Therefore, the challenge we face is how to combine and generalize these approaches, also using explorative and confirmatory methods. On the applicative side, nutritional and food sciences topics are tackled from alternative perspectives, which might converge into either equivalent or competing evidence, characterizing cutting-edge discoveries in these fields in both experimental and observational studies.
The aim of this Special Issue is to emphasize the role of (i) data analysis, (ii) data science, (iii) study design, (iv) sampling methods and (v) questionnaire validation applied to nutritional research and food sciences. Research providing biomedical evidence, as well as theoretical papers introducing links across methods in applied research, are strongly encouraged.
Dr. Davide Guido
Guest Editor
Dr. Antonella Carcagnì
Guest Editor Assistant
Manuscript Submission Information
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Keywords
- nutrition
- food sciences
- biostatistics
- data analysis
- data science
- nutritional epidemiology
- questionnaire validation
- machine learning
- deep learning
- clinical trials and observational studies
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