Body composition prediction by multivariate statistical modeling
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Bester Preis: € 48,93 (vom 26.11.2019)1
Body composition prediction by multivariate statistical modeling
DE PB NW
ISBN: 9783639862157 bzw. 3639862155, in Deutsch, Scholar'S Press, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
buecher.de GmbH & Co. KG, [1].
The assessment of human body composition (BC) is important for evaluating health and nutritional status. Increased fat mass is associated with an increased risk of metabolic diseases declined lean mass or fat-free mass is also directly related to health and particularly with the mortality rate. More importantly, reduction in lean mass occurs together with an increase of body fat during aging therefore assessing these changes in BC may be important because the study will lead to a pre-diagnosis for the prevention of morbidity and mortality risk. Accurate BC measurements can be obtained from DXA and others, but their applications require fixed equipment and are time consuming. Therefore, they are not convenient for routine clinical examinations. Potential uses of statistical methods for BC assessment have been highlighted, we presented in this book a linear and Bayesian network modeling for predicting simultaneously body, trunk and appendicular fat and lean masses based on anthropometric covariables. The main advantages in our proposed multivariate approach consisted in using very simple covariables and enabling to take into account the correlation structure between the response.2016. 200 S. 220 mmVersandfertig in 3-5 Tagen, Softcover.
buecher.de GmbH & Co. KG, [1].
The assessment of human body composition (BC) is important for evaluating health and nutritional status. Increased fat mass is associated with an increased risk of metabolic diseases declined lean mass or fat-free mass is also directly related to health and particularly with the mortality rate. More importantly, reduction in lean mass occurs together with an increase of body fat during aging therefore assessing these changes in BC may be important because the study will lead to a pre-diagnosis for the prevention of morbidity and mortality risk. Accurate BC measurements can be obtained from DXA and others, but their applications require fixed equipment and are time consuming. Therefore, they are not convenient for routine clinical examinations. Potential uses of statistical methods for BC assessment have been highlighted, we presented in this book a linear and Bayesian network modeling for predicting simultaneously body, trunk and appendicular fat and lean masses based on anthropometric covariables. The main advantages in our proposed multivariate approach consisted in using very simple covariables and enabling to take into account the correlation structure between the response.2016. 200 S. 220 mmVersandfertig in 3-5 Tagen, Softcover.
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Body Composition Prediction by Multivariate Statistical Modeling (2016)
DE NW
ISBN: 9783639862157 bzw. 3639862155, in Deutsch, Scholars' Press, neu.
Von Händler/Antiquariat, Books2Anywhere [190245], Fairford, GLOS, United Kingdom.
New Book. Delivered from our UK warehouse in 3 to 5 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
New Book. Delivered from our UK warehouse in 3 to 5 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
3
Body composition prediction by multivariate statistical modeling
DE NW
ISBN: 9783639862157 bzw. 3639862155, in Deutsch, VDM Verlag Dr. Müller, Saarbrücken, Deutschland, neu.
Lieferung aus: Deutschland, zzgl. Versandkosten.
The assessment of human body composition (BC) is important for evaluating health and nutritional status. Increased fat mass is associated with an increased risk of metabolic diseases; declined lean mass or fat-free mass is also directly related to health and particularly with the mortality rate. More importantly, reduction in lean mass occurs together with an increase of body fat during aging; therefore assessing these changes in BC may be important because the study will lead to a pre-diagnosis for the prevention of morbidity and mortality risk. Accurate BC measurements can be obtained from DXA and others, but their applications require fixed equipment and are time consuming. Therefore, they are not convenient for routine clinical examinations. Potential uses of statistical methods for BC assessment have been highlighted, we presented in this book a linear and Bayesian network modeling for predicting simultaneously body, trunk and appendicular fat and lean masses based on anthropometric covariables. The main advantages in our proposed multivariate approach consisted in using very simple covariables and enabling to take into account the correlation structure between the response.
The assessment of human body composition (BC) is important for evaluating health and nutritional status. Increased fat mass is associated with an increased risk of metabolic diseases; declined lean mass or fat-free mass is also directly related to health and particularly with the mortality rate. More importantly, reduction in lean mass occurs together with an increase of body fat during aging; therefore assessing these changes in BC may be important because the study will lead to a pre-diagnosis for the prevention of morbidity and mortality risk. Accurate BC measurements can be obtained from DXA and others, but their applications require fixed equipment and are time consuming. Therefore, they are not convenient for routine clinical examinations. Potential uses of statistical methods for BC assessment have been highlighted, we presented in this book a linear and Bayesian network modeling for predicting simultaneously body, trunk and appendicular fat and lean masses based on anthropometric covariables. The main advantages in our proposed multivariate approach consisted in using very simple covariables and enabling to take into account the correlation structure between the response.
4
Body composition prediction by multivariate statistical modeling
~EN NW AB
ISBN: 9783639862157 bzw. 3639862155, vermutlich in Englisch, VDM Verlag Dr. Müller, Saarbrücken, Deutschland, neu, Hörbuch.
Lieferung aus: Deutschland, Lieferzeit: 5 Tage.
The assessment of human body composition (BC) is important for evaluating health and nutritional status. Increased fat mass is associated with an increased risk of metabolic diseases, declined lean mass or fat-free mass is also directly related to health and particularly with the mortality rate. More importantly, reduction in lean mass occurs together with an increase of body fat during aging, therefore assessing these changes in BC may be important because the study will lead to a pre-diagnosis for the prevention of morbidity and mortality risk. Accurate BC measurements can be obtained from DXA and others, but their applications require fixed equipment and are time consuming. Therefore, they are not convenient for routine clinical examinations. Potential uses of statistical methods for BC assessment have been highlighted, we presented in this book a linear and Bayesian network modeling for predicting simultaneously body, trunk and appendicular fat and lean masses based on anthropometric covariables. The main advantages in our proposed multivariate approach consisted in using very simple covariables and enabling to take into account the correlation structure between the response.
The assessment of human body composition (BC) is important for evaluating health and nutritional status. Increased fat mass is associated with an increased risk of metabolic diseases, declined lean mass or fat-free mass is also directly related to health and particularly with the mortality rate. More importantly, reduction in lean mass occurs together with an increase of body fat during aging, therefore assessing these changes in BC may be important because the study will lead to a pre-diagnosis for the prevention of morbidity and mortality risk. Accurate BC measurements can be obtained from DXA and others, but their applications require fixed equipment and are time consuming. Therefore, they are not convenient for routine clinical examinations. Potential uses of statistical methods for BC assessment have been highlighted, we presented in this book a linear and Bayesian network modeling for predicting simultaneously body, trunk and appendicular fat and lean masses based on anthropometric covariables. The main advantages in our proposed multivariate approach consisted in using very simple covariables and enabling to take into account the correlation structure between the response.
5
Body composition prediction by multivariate statistical modeling
~EN PB NW
ISBN: 9783639862157 bzw. 3639862155, vermutlich in Englisch, SPS, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
Body composition prediction by multivariate statistical modeling: The assessment of human body composition (BC) is important for evaluating health and nutritional status. Increased fat mass is associated with an increased risk of metabolic diseases declined lean mass or fat-free mass is also directly related to health and particularly with the mortality rate. More importantly, reduction in lean mass occurs together with an increase of body fat during aging therefore assessing these changes in BC may be important because the study will lead to a pre-diagnosis for the prevention of morbidity and mortality risk. Accurate BC measurements can be obtained from DXA and others, but their applications require fixed equipment and are time consuming. Therefore, they are not convenient for routine clinical examinations. Potential uses of statistical methods for BC assessment have been highlighted, we presented in this book a linear and Bayesian network modeling for predicting simultaneously body, trunk and appendicular fat and lean masses based on anthropometric covariables. The main advantages in our proposed multivariate approach consisted in using very simple covariables and enabling to take into account the correlation structure between the response. Englisch, Taschenbuch.
Body composition prediction by multivariate statistical modeling: The assessment of human body composition (BC) is important for evaluating health and nutritional status. Increased fat mass is associated with an increased risk of metabolic diseases declined lean mass or fat-free mass is also directly related to health and particularly with the mortality rate. More importantly, reduction in lean mass occurs together with an increase of body fat during aging therefore assessing these changes in BC may be important because the study will lead to a pre-diagnosis for the prevention of morbidity and mortality risk. Accurate BC measurements can be obtained from DXA and others, but their applications require fixed equipment and are time consuming. Therefore, they are not convenient for routine clinical examinations. Potential uses of statistical methods for BC assessment have been highlighted, we presented in this book a linear and Bayesian network modeling for predicting simultaneously body, trunk and appendicular fat and lean masses based on anthropometric covariables. The main advantages in our proposed multivariate approach consisted in using very simple covariables and enabling to take into account the correlation structure between the response. Englisch, Taschenbuch.
6
Body composition prediction by multivariate statistical modeling
~EN PB NW
ISBN: 3639862155 bzw. 9783639862157, vermutlich in Englisch, SPS, Taschenbuch, neu.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
7
Body composition prediction by multivariate statistical modeling (2016)
~EN PB NW
ISBN: 9783639862157 bzw. 3639862155, vermutlich in Englisch, VDM Verlag Dr. Müller, Saarbrücken, Deutschland, Taschenbuch, neu.
Lieferung aus: Deutschland, Next Day, Versandkostenfrei.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
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