scholarly journals The Development of Athlete Performance Capabilities Index (APCI) Model for Male U12 Player Selection using Multivariate Analysis

2018 ◽  
Vol 7 (4.34) ◽  
pp. 97
Author(s):  
Mohamad Razali Abdullah ◽  
Hafizan Juahir ◽  
N. Mohamad Shukri ◽  
N. A. Fuat ◽  
N. A. Mohd Ros ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Factor Score ◽  
Principal Component ◽  
Factor Loading ◽  
Group Classification ◽  
Performance Group ◽  
Two Factors ◽  
Low Performance ◽  
High Factor Loading ◽  
Athlete Performance

This study develops an Athlete Performance Capabilities Index (APCI) model using multivariate analysis for selecting the best player of under twelve (U12).  Measurement of anthropometrics and physical fitness were evaluated among 178 male players aged 12±0.52 years. Factor score derived by Principal Component Analysis were used to obtain a model for APCI and Discriminant Analysis (DA) were conducted to validate the correctness of group classification by APCI. Result was found two factors with eigenvalues greater than 1 were extracted which accounted for 62.00% of the variations present in the original variables. The two factors were used to obtain the factor score coefficients explained by 35.72% and 26.67% of the variations in athlete performance respectively. Factor 1 revealed high factor loading on fitness compared to Factor 2 as it was significantly related to anthropometrics. A model was obtained using standardized coefficient of factor 1. Three clusters of performance were shaped in view by categorizing APCI ≥ 75%, 25% ≤ APCI < 75% and APCI < 25% as high, moderate and low performance group respectively. Three discriminated variables out of thirteen variables were obtained using Forward and Backward stepwise mode of DA, which were weight, standing broad jump, and 40 meters’ speed. Such variables were established as essential indicator for selecting the best player among male U12.   

scholarly journals Phenotypic Variation in Freshwater Murrel,Channa punctatus(Bloch, 1793) from Northern and Eastern Regions of India Using Truss Analysis

2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Ankur Kashyap ◽  
Madhu Awasthi ◽  
Mohammad Serajuddin
Keyword(s):  
Principal Component Analysis ◽  
Multivariate Analysis ◽  
Significant Variation ◽  
Function Analysis ◽  
Principal Component ◽  
Group Classification ◽  
Channa Punctatus ◽  
Morphometric Variation ◽  
Freshwater Murrel ◽  
Confidence Ellipses

Morphometric variation study was carried out using truss analysis in freshwater murrel,Channa punctatus(Bloch, 1793), to explore different phenotypic stocks ofC. punctatus.Significant variation in the morphometric analysis was observed using the truss network and multivariate analysis of the three subpopulations of freshwater murrel,C. punctatus, from the two different regions of India. Principal component analysis accounted for a total variation of 91.95% by the first three principal components. PC 1 represented the variation due to size and PC 2 and PC 3 represented variations due to shape. The 95% confidence ellipses depicted the clear isolation between the samples in scatter graph of PC 1 on PC 2. The combined groups plot (DF 1 on DF 2) based on discriminant function analysis (DFA) also validated the existence of three different subpopulations. In group classification using DFA, 100 percent of all the samples were correctly classified into their original subpopulation. These results support the existence of multiracial composition ofC. punctatusacross the different geographical isolated sites and, thus, these findings indicate the presence of three different phenotypic stocks ofC. punctatus.

scholarly journals Dietary patterns and whole grain cereals in the Scandinavian countries – differences and similarities. The HELGA project

2014 ◽  
Vol 18 (5) ◽  
pp. 905-915 ◽  
Author(s):  
Dagrun Engeset ◽  
Dag Hofoss ◽  
Lena M Nilsson ◽  
Anja Olsen ◽  
Anne Tjønneland ◽  
...  
Keyword(s):  
Dietary Patterns ◽  
Principal Component ◽  
Factor Loading ◽  
Health Study ◽  
Food Groups ◽  
Whole Grain ◽  
Food Items ◽  
Diet Pattern ◽  
Study Population ◽  
High Factor Loading

AbstractObjectiveTo identify dietary patterns with whole grains as a main focus to see if there is a similar whole grain pattern in the three Scandinavian countries; Denmark, Sweden and Norway. Another objective is to see if items suggested for a Nordic Food Index will form a typical Nordic pattern when using factor analysis.SettingThe HELGA study population is based on samples of existing cohorts: the Norwegian Women and Cancer Study, the Swedish Västerbotten cohort and the Danish Diet, Cancer and Health study. The HELGA study aims to generate knowledge about the health effects of whole grain foods.SubjectsThe study included a total of 119 913 participants.DesignThe associations among food variables from FFQ were investigated by principal component analysis. Only food groups common for all three cohorts were included. High factor loading of a food item shows high correlation of the item to the specific diet pattern.ResultsThe main whole grain for Denmark and Sweden was rye, while Norway had highest consumption of wheat. Three similar patterns were found: a cereal pattern, a meat pattern and a bread pattern. However, even if the patterns look similar, the food items belonging to the patterns differ between countries.ConclusionsHigh loadings on breakfast cereals and whole grain oat were common in the cereal patterns for all three countries. Thus, the cereal pattern may be considered a common Scandinavian whole grain pattern. Food items belonging to a Nordic Food Index were distributed between different patterns.

scholarly journals Determining Youth Profile using Principle Component Analysis for Identifying Talent in Sports

2019 ◽  
Vol 8 (2S7) ◽  
pp. 212-215
Keyword(s):  
Decision Making ◽  
Principal Component Analysis ◽  
Principal Component ◽  
Factor Loading ◽  
Component Analysis ◽  
Talent Identification ◽  
Sitting Height ◽  
Data Analyses ◽  
Program Data ◽  
High Factor Loading

This study attempts to determine youth profile in sports talent identification program. Data of anthropometric and physical fitness included power, agility, speeds, flexibility, strength and endurance were obtained from 600 participants in a sports talent identification program aged 13-15 years. Data analyses were carried out using multivariate analysis of principal component analysis (PCA). PCA revealed three principal components with 71.5% total variation for this studied group. The first component consists of high factor loading in speed variables (10 meter run, 20 meter run, 40 meter run) and endurance (predicted VO₂ max). The second component was constituted by anthropometric variables (weight, height, sitting height and armspan). While third component contains flexibility variable (sit and reach). These selected variables of anthropometric and fitness are, therefore, revealed as the essential attributes those must be prioritized for a talent scouting in sports. Present results had demonstrated youth profile that capable of providing an information that could help coaches in decision making during athlete selection in sports talent identification.

Factors Influencing Food Ordering on Zomato in Hisar District, Haryana

2020 ◽  
Vol 36 (2) ◽  
pp. 46-49
Author(s):  
Shakshi K ◽  
Megha Goyal ◽  
Suman Ghalawat ◽  
Nitin Kumar
Keyword(s):  
Factor Analysis ◽  
Factor Loading ◽  
Survey Question ◽  
Cronbach Alpha ◽  
Online Mode ◽  
Factors Influencing ◽  
Two Factors ◽  
Quality Of Food ◽  
High Factor Loading

The present study was conducted to investigate the factors influencing food ordering on Zomato in Hisar region of Haryana. A survey was conducted on 100 respondents by using questionnaire as research instrument through online mode. Pie charts were plotted for studying behavior of demographic characters and bar diagrams were used for finding the influence of factors under study. The validity & reliability of a questionnaire measuring an attitude and attitude related aspects was tested with exploratory factor analysis and Cronbach’s alpha The factor analysis with thirteen observed variables (i.e., survey question responses) that was summarized in terms of two factors with Cronbach alpha values .930 & .902. Cronbach alpha for both the factors was greater than 0.9, hence questionnaire was reliable and strength of factor 1 was more with higher value of Cronbach alpha. It is concluded that offers, price, quality of food and delivery charges was effective variables with high factor loading.

Effects of an Anxiety-Specific Psychometric Factor on Fear Conditioning and Fear Generalization

2017 ◽  
Vol 225 (3) ◽  
pp. 200-213 ◽  
Author(s):  
Christian Baumann ◽  
Miriam A. Schiele ◽  
Martin J. Herrmann ◽  
Tina B. Lonsdorf ◽  
Peter Zwanzger ◽  
...  
Keyword(s):  
Risk Factor ◽  
Anxiety Disorders ◽  
Fear Conditioning ◽  
Longitudinal Design ◽  
Principal Component ◽  
Anxiety And Depression ◽  
Specific Factor ◽  
High Anxious ◽  
Two Factors ◽  
Fear Generalization

Abstract. Conditioning and generalization of fear are assumed to play central roles in the pathogenesis of anxiety disorders. Here we investigate the influence of a psychometric anxiety-specific factor on these two processes, thus try to identify a potential risk factor for the development of anxiety disorders. To this end, 126 healthy participants were examined with questionnaires assessing symptoms of anxiety and depression and with a fear conditioning and generalization paradigm. A principal component analysis of the questionnaire data identified two factors representing the constructs anxiety and depression. Variations in fear conditioning and fear generalization were solely associated with the anxiety factor characterized by anxiety sensitivity and agoraphobic cognitions; high-anxious individuals exhibited stronger fear responses (arousal) during conditioning and stronger generalization effects for valence and UCS-expectancy ratings. Thus, the revealed psychometric factor “anxiety” was associated with enhanced fear generalization, an assumed risk factor for anxiety disorders. These results ask for replication with a longitudinal design allowing to examine their predictive validity.

Principal component analysis of substituent constants

1990 ◽  
Vol 55 (1) ◽  
pp. 55-62 ◽  
Author(s):  
Drahomír Hnyk
Keyword(s):  
Principal Component Analysis ◽  
Inductive Effect ◽  
Resonance Effect ◽  
Principal Component ◽  
Component Analysis ◽  
Total Variance ◽  
Data Matrix ◽  
Cumulative Proportion ◽  
Two Factors ◽  
Substituent Constants

The principal component analysis has been applied to a data matrix formed by 7 usual substituent constants for 38 substituents. Three factors are able to explain 99.4% cumulative proportion of total variance. Several rotations have been carried out for the first two factors in order to obtain their physical meaning. The first factor is related to the resonance effect, whereas the second one expresses the inductive effect, and both together describe 97.5% cumulative proportion of total variance. Their mutual orthogonality does not directly follow from the rotations carried out. With the help of these factors the substituents are divided into four main classes, and some of them assume a special position.

scholarly journals STATISTICAL MULTIVARIATE ANALYSIS APPLIED TO ENVIRONMENTAL CHARACTERIZATION OF SOIL IN SEMIARID REGION1

2019 ◽  
Vol 32 (1) ◽  
pp. 200-210
Author(s):  
Antônio Italcy de Oliveira Júnior ◽  
Luiz Alberto Ribeiro Mendonça ◽  
Sávio de Brito Fontenele ◽  
Adriana Oliveira Araújo ◽  
Maria Gorethe de Sousa Lima Brito
Keyword(s):  
Organic Matter Content ◽  
Principal Component ◽  
Matter Content ◽  
Multivariate Statistical ◽  
Statistical Tool ◽  
Environmental Characterization ◽  
Hierarchical Grouping ◽  
Two Factors ◽  
Total Data

ABSTRACT Soil is a dynamic and complex system that requires a considerable number of samples for analysis and research purposes. Using multivariate statistical methods, favorable conditions can be created by analyzing the samples, i.e., structural reduction and simplification of the data. The objective of this study was to use multivariate statistical analysis, including factorial analysis (FA) and hierarchical groupings, for the environmental characterization of soils in semiarid regions, considering anthropic (land use and occupation) and topographic aspects (altitude, moisture, granulometry, PR, and organic-matter content). As a case study, the São José Hydrographic Microbasin, which is located in the Cariri region of Ceará, was considered. An FA was performed using the principal component method, with normalized varimax rotation. In hierarchical grouping analysis, the “farthest neighbor” method was used as the hierarchical criterion for grouping, with the measure of dissimilarity given by the “square Euclidean distance.” The FA indicated that two factors explain 75.76% of the total data variance. In the analysis of hierarchical groupings, the samples were agglomerated in three groups with similar characteristics: one with samples collected in an area of the preserved forest and two with samples collected in areas with more anthropized soils. This indicates that the statistical tool used showed sensitivity to distinguish the most conserved soils and soils with different levels of anthropization.

The Effects of Low Performance Group and Individual Contingencies on Cooperative Behaviors Exhibited by Fifth Graders

1972 ◽  
Vol 22 (3) ◽  
pp. 359-368 ◽  
Author(s):  
John S. Wodarski ◽  
Robert L. Hamblin ◽  
David R. Buckholdt ◽  
Daniel E. Ferritor
Keyword(s):  
Fifth Graders ◽  
Performance Group ◽  
Cooperative Behaviors ◽  
Low Performance

Use of the Perceived Physical Competence Scale with Adolescents with Disabilities

1995 ◽  
Vol 80 (2) ◽  
pp. 571-577 ◽  
Author(s):  
Taru Lintunen ◽  
Pilvikki Heikinaro-Johansson ◽  
Claudine Sherrill
Keyword(s):  
Gender Differences ◽  
Factor Analysis ◽  
Principal Component ◽  
Principal Component Factor Analysis ◽  
Validity And Reliability ◽  
Varimax Rotation ◽  
Physical Competence ◽  
Related Literature ◽  
Competence Scale ◽  
Two Factors

The construct validity and reliability of the 1987 Perceived Physical Competence Scale of Lintunen were examined to assess the applicability of the instrument for use with adolescents with disabilities. Subjects were 51 girls and 34 boys ( M age = 15.1 yr.) from several schools in central Finland. Principal component factor analysis with varimax rotation yielded the same two factors for adolescents with disabilities as reported for nondisabled adolescents in the related literature. Cronbach alphas for the two factors were .89 and .56. It was concluded that the scale is an appropriate measure for adolescents with disabilities. Statistical analysis indicated no gender differences for adolescents with disabilities. When compared with nondisabled groups in the related literature, these adolescents had perceived fitness similar to nondisabled peers but significantly lower than that of athletes without disabilities.

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