A multivariate statistical approach to the assessment of nutrition status
| dc.contributor.advisor | Troskie, Casper G | |
| dc.contributor.author | Fellingham, Stephen A | |
| dc.date.accessioned | 2020-05-29T13:13:47Z | |
| dc.date.available | 2020-05-29T13:13:47Z | |
| dc.date.issued | 1972 | |
| dc.date.updated | 2020-04-07T07:39:33Z | |
| dc.description.abstract | Attention is drawn to the confusion which surrounds the concept of nutrition status and the problem of selecting an optimum subset of variables by which nutrition status can best be assessed is defined. Using a multidisciplinary data set of some 60 variables observed on 1898 school children from four racial groups, the study aims to identify statistically, both those variables which are unrelated to nutrition status and also those which, although related, are so highly correlated that the measurement of all would be an unnecessary extravagance. It is found that, while the somatometric variables provide a reasonably good (but non-specific) estimate of nutrition status, the disciplines form meaningful groups and the variables of the various disciplines tend to supplement rather than replicate each other. Certain variables from most of the disciplines are, therefore, necessary for an optimum and specific estimate of nutrition status. Both the potential and the shortcomings of a number of statistical techniques are demonstrated. | |
| dc.identifier.apacitation | Fellingham, S. A. (1972). <i>A multivariate statistical approach to the assessment of nutrition status</i>. (). ,Faculty of Science ,Department of Statistical Sciences. Retrieved from | en_ZA |
| dc.identifier.chicagocitation | Fellingham, Stephen A. <i>"A multivariate statistical approach to the assessment of nutrition status."</i> ., ,Faculty of Science ,Department of Statistical Sciences, 1972. | en_ZA |
| dc.identifier.citation | Fellingham, S.A. 1972. A multivariate statistical approach to the assessment of nutrition status. . ,Faculty of Science ,Department of Statistical Sciences. | en_ZA |
| dc.identifier.ris | TY - Thesis / Dissertation AU - Fellingham, Stephen A AB - Attention is drawn to the confusion which surrounds the concept of nutrition status and the problem of selecting an optimum subset of variables by which nutrition status can best be assessed is defined. Using a multidisciplinary data set of some 60 variables observed on 1898 school children from four racial groups, the study aims to identify statistically, both those variables which are unrelated to nutrition status and also those which, although related, are so highly correlated that the measurement of all would be an unnecessary extravagance. It is found that, while the somatometric variables provide a reasonably good (but non-specific) estimate of nutrition status, the disciplines form meaningful groups and the variables of the various disciplines tend to supplement rather than replicate each other. Certain variables from most of the disciplines are, therefore, necessary for an optimum and specific estimate of nutrition status. Both the potential and the shortcomings of a number of statistical techniques are demonstrated. DA - 1972 DB - OpenUCT DP - University of Cape Town KW - Statistical Sciences KW - Nutrition LK - https://open.uct.ac.za PY - 1972 T1 - A multivariate statistical approach to the assessment of nutrition status TI - A multivariate statistical approach to the assessment of nutrition status UR - ER - | en_ZA |
| dc.identifier.uri | https://hdl.handle.net/11427/32011 | |
| dc.identifier.vancouvercitation | Fellingham SA. A multivariate statistical approach to the assessment of nutrition status. []. ,Faculty of Science ,Department of Statistical Sciences, 1972 [cited yyyy month dd]. Available from: | en_ZA |
| dc.language.rfc3066 | eng | |
| dc.publisher.department | Department of Statistical Sciences | |
| dc.publisher.faculty | Faculty of Science | |
| dc.subject | Statistical Sciences | |
| dc.subject | Nutrition | |
| dc.title | A multivariate statistical approach to the assessment of nutrition status | |
| dc.type | Doctoral Thesis | |
| dc.type.qualificationlevel | Doctoral |