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Nutrient Data Analysis Techniques and Strategies
| Content Provider | Scilit |
|---|---|
| Copyright Year | 2001 |
| Description | Analyses of nutrient data pose special challenges to investigators. In such analyses, investigators need to consider:1. Possible over-or under-reporting of intakes, leading to “impossible” or extreme values in the data set2. How to adjust for total energy intake 3. How to model nutrients, e.g., as continuous or categorical variable 4. How to avoid multicollinearity, particularly when nutrients are expressed inabsolute amounts, e.g., grams/day 5. How to analyze dietary supplement data 6. How to account for large day-to-day variability in intakes, which can lead tomisclassification of individuals with respect to usual intakeThe objectives of this section are to examine various approaches to addressing the above issues; to briefly describe the common types of observational and experimental studies that collect nutritional data; and to describe the most common methods of analysis used in the types of studies described. Book Name: Handbook of Nutrition and Food |
| Related Links | https://api.taylorfrancis.com/content/chapters/edit/download?identifierName=doi&identifierValue=10.1201/9781420038392-34&type=chapterpdf |
| Ending Page | 644 |
| Page Count | 14 |
| Starting Page | 631 |
| DOI | 10.1201/9781420038392-34 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2001-10-30 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Handbook of Nutrition and Food Nutrition and Dietetics Categorical Variable Nutrient Data Extreme Nutrients Analysis Nutritional Data Data Set2 Avoid Multicollinearity |
| Content Type | Text |
| Resource Type | Chapter |
