Predicting child nutritional status using related socioeconomic variables—application of discriminant function analysis

2022 ◽  
pp. 381-432
Author(s):  
Suresh C. Babu ◽  
Shailendra N. Gajanan
Keyword(s):  
Nutritional Status ◽  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
Function Analysis ◽  
Socioeconomic Variables ◽  
Child Nutritional Status

scholarly journals Nutritional Status of Fishermen Communities: Validation of Conventional Methods with Discriminant Function Analysis

2014 ◽  
Vol 8 ◽  
pp. 49-59 ◽  
Author(s):  
Baidyanath Pal ◽  
Babulal Seal ◽  
Subrata K. Roy
Keyword(s):  
Nutritional Status ◽  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
Function Analysis ◽  
Energy Deficiency ◽  
Under Nutrition ◽  
Chronic Energy Deficiency ◽  
Arm Circumference ◽  
Conventional Methods ◽  
Mid Upper Arm Circumference

Anthropological methods of assessing nutritional status of adults have been reinvestigated. Objective of the study is to detect the predictor variables that discriminate for under nutrition or Chronic Energy Deficiency (CED) by two conventional methods e.g. Body Mass Index (BMI) and Mid Upper Arm Circumference (MUAC). Discriminant function analysis was used to build valid and accurate predictive model for evaluating nutritional status. Anthropometric measurements were collected using standard techniques and used as independent variables. Recommended cut-off values of BMI and MUAC was used for evaluating nutritional status. The extent of CED (BMI < 18.5) was found 43.50% and prevalence of under-nutrition in terms of MUAC (MUAC < 23.0 cm for Male and < 22.0 cm for Female) was 21.7%. Discriminant function analysis reveals that 85.7% and 72.0% individuals were classified correctly in terms of nutritional status. Therefore, BMI is the good indicator for detecting malnutrition. Fat mass discriminates between groups.

Diagnoses Generated by Numerical Taxonomic Methods Applied to Standard Blood Variables

1980 ◽  
Vol 19 (04) ◽  
pp. 205-209
Author(s):  
L. A. Abbott ◽  
J. B. Mitton
Keyword(s):  
Liver Cirrhosis ◽  
Renal Disease ◽  
Principal Components Analysis ◽  
Discriminant Function ◽  
Principal Components ◽  
Discriminant Function Analysis ◽  
Chronic Renal Disease ◽  
Function Analysis ◽  
Infectious Hepatitis ◽  
Components Analysis

Data taken from the blood of 262 patients diagnosed for malabsorption, elective cholecystectomy, acute cholecystitis, infectious hepatitis, liver cirrhosis, or chronic renal disease were analyzed with three numerical taxonomy (NT) methods : cluster analysis, principal components analysis, and discriminant function analysis. Principal components analysis revealed discrete clusters of patients suffering from chronic renal disease, liver cirrhosis, and infectious hepatitis, which could be displayed by NT clustering as well as by plotting, but other disease groups were poorly defined. Sharper resolution of the same disease groups was attained by discriminant function analysis.

scholarly journals Description of Echolocation Call Parameters for Urban Bats in Vietnam as a Step Towards a More Integrated Acoustic Monitoring of Urban Wildlife in Southeast Asia

Diversity ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 18
Author(s):  
Long Kim Pham ◽  
Bang Van Tran ◽  
Quy Tan Le ◽  
Trung Thanh Nguyen ◽  
Christian C. Voigt
Keyword(s):  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
Function Analysis ◽  
Quantitative Description ◽  
Southeast Asian ◽  
Asian Countries ◽  
Echolocation Call ◽  
Echolocation Calls ◽  
Pilot Work ◽  
Southeast Asian Countries

This study is the first step towards more systematic monitoring of urban bat fauna in Vietnam and other Southeast Asian countries by collecting bat echolocation call parameters in Ho Chi Minh and Tra Vinh cities. We captured urban bats and then recorded echolocation calls after releasing in a tent. Additional bat’s echolocation calls from the free-flying bats were recorded at the site where we captured bat. We used the obtained echolocation call parameters for a discriminant function analysis to test the accuracy of classifying these species based on their echolocation call parameters. Data from this pilot work revealed a low level of diversity for the studied bat assemblages. Additionally, the discriminant function analysis successfully classified bats to four bat species with an accuracy of >87.4%. On average, species assignments were correct for all calls from Taphozous melanopogon (100% success rate), for 70% of calls from Pipistrellus javanicus, for 80.8% of calls from Myotis hasseltii and 67.3% of calls from Scotophilus kuhlii. Our study comprises the first quantitative description of echolocation call parameters for urban bats of Vietnam. The success in classifying urban bats based on their echolocation call parameters provides a promising baseline for monitoring the effect of urbanization on bat assemblages in Vietnam and potentially also other Southeast Asian countries.

Mineralogy of Egyptian Bentonitic Clays I: Discriminant Function Analysis

2012 ◽  
Vol 60 (4) ◽  
pp. 387-404 ◽  
Author(s):  
Mohamed Agha ◽  
Ray E. Ferrell ◽  
George F. Hart
Keyword(s):  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
Function Analysis

Using discriminant function analysis to identify Holocene tephras based on magnetite composition: a case study from the Sunwapta Pass area, Jasper National Park

1986 ◽  
Vol 23 (6) ◽  
pp. 804-812 ◽  
Author(s):  
A. B. Beaudoin ◽  
R. H. King
Keyword(s):  
National Parks ◽  
Discriminant Function ◽  
Discriminant Function Analysis ◽  
National Park ◽  
Function Analysis ◽  
Classification Schemes ◽  
Jasper National Park ◽  
Multivariate Method ◽  
Reference Samples

The magnetite composition from three sets of samples of Mazama, St. Helens set Y, and Bridge River tephras from Jasper and Banff national parks are used to test whether discriminant function analysis can unambiguously distinguish these tephras. The multivariate method is found to be very sensitive to the change in reference samples. St. Helens set Y tephra is clearly distinguished. However, discrimination between Mazama and Bridge River tephras is less distinct. A set of unknown tephras from the Sunwapta Pass area was used to test the classification schemes. Unknown tephras are assigned to different tephra types depending on which reference tephra set is used in the discriminant function analysis.

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