scholarly journals Bartlett factor scores in multiple linear regression equation as a tool for estimating economic traits in broilers

Stočarstvo ◽  
2017 ◽  
Vol 71 (1-2) ◽  
pp. 20-28
Author(s):  
Jesuyon Oluwatosin Mawunapon Adegoke
Keyword(s):  
Body Weight ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Live Weight ◽  
Consumer Preference ◽  
Regression Equation ◽  
Abdominal Circumference ◽  
Factor Scores ◽  
Economic Traits ◽  
Factor Regression

To propose a simpler tool that eliminates the age-long problems associated with the traditional index method for selection of multiple traits in broilers, the Barttlet factor regression equation is being proposed as an alternative selection tool. 100 day-old chicks each of Arbor Acres (AA) and Annak (AN) broiler strains were obtained from two rival hatcheries in Ibadan Nigeria. These were raised on deep litter system in a 56-day feeding trial in the University of Ibadan Teaching and Research Farm, located in South-west Tropical Nigeria. The body weight and body dimensions were measured and recorded during the trial period. Eight (8) zoometric measurements namely Live weight (g), Abdominal Circumference, Abdominal length, Breast width, leg length, Height, Wing length and Thigh circumference (all in cm) were recorded randomly from 20 birds within strain, at a fixed time on the first day of the new week respectively with a 5-kg capacity Camry scale. These records were analyzed and compared using completely randomized design (CRD) of SPSS analytical software, with the means procedure, Factor Scores (FS) in stepwise Multiple Linear Regression (MLR) procedure for initial live weight equations. Bartlett Factor Score (BFS) analysis extracted 2 factors for each strain, termed Body-length and Thigh-meatiness Factors for AA, and; Breast Size and Height Factors for AN. These derived orthogonal factors assisted in deducing and comparing trait-combinations that best describe body conformation and Meatiness in experimental broilers. BFS procedure yielded different body conformational traits for the two strains, thus indicating the different economic traits and advantages of strains. These Factors could be useful as selection criteria for improving desired economic traits. The final Bartlett Factor Regression equations for prediction of body weight were highly significant with P<0.0001, R2 of 0.92 and above, VIF of 1.00, and DW of 1.90 and 1.47 for Arbor Acres and Annak respectively. These FSR equations could be used as a simple and potent tool for selection during poultry flock improvement, it could also be used to estimate selection index of flocks to discriminate between strains, and evaluate consumer preference traits in broilers.

scholarly journals Magnetization Transfer Ratio of Peripheral Nerve and Skeletal Muscle

2021 ◽  
Author(s):  
Olivia Fösleitner ◽  
Véronique Schwehr ◽  
Tim Godel ◽  
Fabian Preisner ◽  
Philipp Bäumer ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Body Weight ◽  
Sciatic Nerve ◽  
Linear Regression ◽  
Peripheral Nerve ◽  
Regression Model ◽  
Multiple Linear Regression ◽  
Linear Regression Model ◽  
Magnetization Transfer ◽  
Multiple Linear Regression Model

Abstract Purpose To assess the correlation of peripheral nerve and skeletal muscle magnetization transfer ratio (MTR) with demographic variables. Methods In this study 59 healthy adults evenly distributed across 6 decades (mean age 50.5 years ±17.1, 29 women) underwent magnetization transfer imaging and high-resolution T2-weighted imaging of the sciatic nerve at 3 T. Mean sciatic nerve MTR as well as MTR of biceps femoris and vastus lateralis muscles were calculated based on manual segmentation on six representative slices. Correlations of MTR with age, body height, body weight, and body mass index (BMI) were expressed by Pearson coefficients. Best predictors for nerve and muscle MTR were determined using a multiple linear regression model with forward variable selection and fivefold cross-validation. Results Sciatic nerve MTR showed significant negative correlations with age (r = −0.47, p < 0.001), BMI (r = −0.44, p < 0.001), and body weight (r = −0.36, p = 0.006) but not with body height (p = 0.55). The multiple linear regression model determined age and BMI as best predictors for nerve MTR (R2 = 0.40). The MTR values were different between nerve and muscle tissue (p < 0.0001), but similar between muscles. Muscle MTR was associated with BMI (r = −0.46, p < 0.001 and r = −0.40, p = 0.002) and body weight (r = −0.36, p = 0.005 and r = −0.28, p = 0.035). The BMI was selected as best predictor for mean muscle MTR in the multiple linear regression model (R2 = 0.26). Conclusion Peripheral nerve MTR decreases with higher age and BMI. Studies that assess peripheral nerve MTR should consider age and BMI effects. Skeletal muscle MTR is primarily associated with BMI but overall less dependent on demographic variables.

scholarly journals Weight and height prediction of immobilized patients

2006 ◽  
Vol 19 (6) ◽  
pp. 655-661 ◽  
Author(s):  
Estela Iraci Rabito ◽  
Gabriela Bergamini Vannucchi ◽  
Vivian Marques Miguel Suen ◽  
Laércio Lopes Castilho Neto ◽  
Júlio Sérgio Marchini
Keyword(s):  
Linear Regression ◽  
Multiple Linear Regression ◽  
Hospitalized Patients ◽  
Anthropometric Measurements ◽  
Abdominal Circumference ◽  
Calf Circumference ◽  
Mean Error ◽  
Arm Circumference ◽  
Height Prediction ◽  
The One

OBJECTIVE: To confirm the adequacy of the formula suggested in the literature and/or to develop appropriate equations for the Brazilian population of immobilized patients based on simple anthropometric measurements. METHODS: Hospitalized patients were submitted to anthropometry and methods to estimate weight and height of bedridden patients were developed by multiple linear regression. RESULTS: Three hundred sixty eight persons were evaluated at two hospital centers and five weight-predicting and two height-predicting equations were developed from the measurements obtained. Among the new equations developed, the simplest one for weight estimate was: Weight (kg) = 0.5759 x (arm circumference, cm) + 0.5263 x (abdominal circumference, cm) + 1.2452 x (calf circumference, cm) -4.8689 x (Sex, male = 1 and female = 2) -32.9241 (r = 0.94); and the one for height estimate was: Height (cm) = 58.6940 - 2.9740 x (Sex) -0.0736 x (age, years) + 0.4958 x (arm length, cm) + 1.1320 x (half- span, cm) (r = 0.88). The estimates thus calculated did not differ significantly from actual measurements, with p = 0.94 and 0.89 and a mean error of 6.0 and 2.1% for weight and height, respectively. CONCLUSION: We suggest that these equations can be used to estimate the weight and height of bedridden patients when necessary or when these parameters cannot be measured with a scale and a stadiometer.

scholarly journals The Influence Of Motivation And Discipline On The Work Productivity Of Employees In Camat Office Of Sukaraja District, Seluma Province, Bengkulu Province

2021 ◽  
Vol 2 (1) ◽  
pp. 1-12
Author(s):  
Ida Ayu Made Er Meytha Gayatri ◽  
Mimi Kurnia Nengsih
Keyword(s):  
Linear Regression ◽  
Hypothesis Testing ◽  
Multiple Linear Regression ◽  
Work Productivity ◽  
Positive Influence ◽  
Regression Equation ◽  
Head Office ◽  
Regression Test

The purpose of this study was to determine factors such as motivation and work discipline tahat affect the work prductivity of employees at the Head Office of Sukaraja District, Seluma Regency. The sample in this study was 29 employees at the Head Office of Sukaraja District, Seluma Regency. Data collectiion using a questionnaire and the method of analysis used is multiple linear regression, test of determination and hypothesis testing. The result of the regression equation is Y = n10,107 + 0,417 X1 + 0,361X2 + e, which means that motivation and work discipline have a positive influence of the work productivity of employees at the Head Office of Sukaraja District, Seluma Regency. The results of the determination test was 0,567 0r (56,7%). This shows that motivation and work discipline have an effect on the work  productivity of employees at the Subdistrict Head Office of Sukaraja District, Seluma Regency by 56,7 % while the rest are explained or influenced by other variables not examined.

scholarly journals PENGARUH KUALITAS PRODUK TERHADAP KEPUTUSAN KONSUMEN MEMBELI MOBIL MEREK TOYOTA AGYA DI KOTA PALU (PT. HADJI KALLA)

2020 ◽  
Vol 2 (2) ◽  
pp. 107-116
Author(s):  
Rizcky Ardiansyah ◽  
Rosida P Adam ◽  
Bakri Hasanuddin
Keyword(s):  
Decision Making ◽  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Product Quality ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Regression Equation ◽  
Analysis Tool

The objective of the research is to find out and analyze the influence of product quality on decision-making, both simultaneously and partially. The research is verificative. The sample involves consumers of Agya car at PT. Hadji Kalla. The analysis tool used is multiple linear regression analysis. The result of regression equation from the study is -2.887 + 0,237 X1+ 0,220X2 + 0,217X3 + 0,319X4 + 0,166X5 + 0,418X6 + 0,140X7. Product Quality partially has significant to decision-making.                                 Tujuan dari penelitian ini adalah untuk mengetahui dan menganalisis pengaruh Kualitas Produk keputusan menandai baik secara simultan maupun parsial. Penelitian ini merupakan penelitian verifikatif. sampel adalah konsumen Of Agya di PT. Hadji Kalla. Alat analisis yang digunakan adalah beberapa analisis regresi linear. Hasil persamaan regresi dari penelitian ini adalah -2,887 + 0.237 X1 + 0,220X2 + 0,217X3 + 0,319X4 + 0,166X5 + 0,418X6 + 0,140X7. Kualitas produk parsial memiliki signifikan untuk pembuatan keputusan.

Characterization of Fabric Friction Performance by CHES-FY System

2013 ◽  
Vol 821-822 ◽  
pp. 1492-1498 ◽  
Author(s):  
Rui Qiang Gao ◽  
Zhao Qun Du ◽  
Wei Dong Yu
Keyword(s):  
Linear Regression ◽  
Correlation Analysis ◽  
Multiple Linear Regression ◽  
Surface Friction ◽  
Regression Equation ◽  
New Apparatus ◽  
Friction Performance ◽  
Fabric Surface ◽  
Orthogonal Tests

The paper mainly introduces a new apparatus (CHES-FY) to measure fabric surface friction. Compacted with the KES-FB system, the CHES-FY system has its own superiority. Through designing orthogonal tests, corresponding properties of 16 groups fabrics were measured by CHES-FY system. Based on the correlation analysis between KES-FB system with CHES-FY system, it indicates that the two systems have high correlations. Thereafter, regression equation that includes four parameters through multiple linear regression were achieved. It reports that CHES-FY system is feasible and accurate in measuring fabric surface friction performance.

scholarly journals PENGARUH MOTIVASI KERJA DAN DISIPLIN KERJA TERHADAP KINERJA KARYAWAN

2019 ◽  
Author(s):  
fayola issalillah
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Significant Influence ◽  
Work Motivation ◽  
Employee Performance ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Regression Equation

ABSTRACT This study aims to determine the motivation variables have a significant effect on performance and work discipline has a significant effect on performance. The sample in this study was 30 respondents and used multiple linear regression analysis with the following regression equation Y Y = 4.604 + 0.476X1 + 0.336X2 + e. From the regression equation it can be seen that the work motivation variable is stated to have a significant influence on employee performance. It can also be said that the more work motivation will affect employee performance. Work discipline variables have an influence on employee performance (Y). This means, every time there is an increase in work discipline will improve employee performance.. Keywords: motivation, discipline, performance ABSTRAKSIPenelitian ini bertujuan untuk mengetahui variabel motivasi berpengaruh signifikan terhadap kinerja dan displin kerja berpengaruh signifikan terhadap kinerja. Sampel dalam penelitian ini adalah 30 responden dan menggunakan analisis regresi linier berganda dengan persamaan regresi sebagai berikut Y = 4,604 + 0,476X1 + 0,336X2 + e. Dari persamaan regresi tersebut dapat diketahui bahwa variabel Motivasi kerja dinyatakan terdapat pengaruh signifikan terhadap kinerja karyawan. Dapat pula dikatakan bahwa semakin motivasi kerja maka akan mempengaruhi kinerja karyawan. Variabel disiplin kerja mempunyai pengaruh terhadap kinerja karyawan (Y). Hal ini berarti, setiap ada peningkatan disiplin kerja akan meningkatkan kinerja karyawan. Kata kunci: motivasi, disiplin, kinerja

scholarly journals Weight loss and usage of an online commercial weight loss program delivered in an everyday context: A 5-year evaluation of the CSIRO Total Wellbeing Diet Online (Preprint)

2020 ◽  
Author(s):  
Gilly A Hendrie ◽  
Danielle L Baird ◽  
Emily Brindal ◽  
Gemma Williams ◽  
Jennie Brand-Miller ◽  
...  
Keyword(s):  
Weight Loss ◽  
Body Weight ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Comprehensive Evaluation ◽  
Economic Benefits ◽  
Weight Loss Program ◽  
Average Weight ◽  
Global Public Health ◽  
Food Diary

BACKGROUND Obesity is a global public health challenge, and there is a need for more evidence-based self-management programs that support longer term, sustained weight loss. OBJECTIVE This study used data from the CSIRO Total Wellbeing Diet Online to determine the reach and weight loss results over its first five years. METHODS Participants were adults who joined the commercial weight loss program of their own volition between October 2014 and September 2019 (N=61,164). Information collected included year of birth, sex, height and weight, and usage data, for example entries into the food diary, views of the menu and program content. Weight loss and percentage of starting body weight lost were calculated. Members were divided into two groups for analysis: ‘Stayers’ were members who signed up to at least 12 weeks of the program and recorded a weight entry at baseline and at the end of the program; ‘Starters’ started the program but did not record a weight after 12 weeks. Descriptive statistics and multiple linear regression were used to describe weight loss and determine the member and program characteristics associated with weight loss. RESULTS Data were available from 59,686 members for analysis. Members were predominately female (n=48979/59686; 82%) with an average age of 50 years (SD=12.6). The average starting weight was 90.2kg (SD=19.7) and over half of all members were obese (n=34195/59688, 57%). At week-12, 95% of members had an active program membership which decreased to 41% at 24 weeks. At week 12, 52% of remaining members were actively using the platform, and by week 24, 27% were using the platform. The average weight loss for all members was 2.8kg or 3.1% of starting body weight. Stayers lost 4.9kg (5.3% of starting body weight), compared to starters who lost 1.6kg (1.7% of starting body weight). Almost half (49%) the members who stayed on the program lost 5% or more of their starting body weight, and 16% achieved a weight loss of 10% or more. Of members who were Class 1 obese when they joined the program, 41% who stayed on the program were no longer obese at the end, and across all categories of obesity 24% were no longer obese at the end of the program. Based on multiple linear regression, platform usage was the strongest predictor of weight loss (beta=.263; P<.001), with higher usage associated with greater weight loss. CONCLUSIONS This comprehensive evaluation of a commercial, online weight loss program showed that it was effective for weight loss, particularly for members who finished the program and were active in using the platform and tools provided. If the results demonstrated here can be achieved at an even greater scale, the potential social and economic benefits will be extremely significant. CLINICALTRIAL not applicable.

scholarly journals Association of gestational diabetes mellitus with offspring weight status across infancy: a prospective birth cohort study in China

2020 ◽  
Author(s):  
Jiajin Hu ◽  
Yilin Liu ◽  
Xiaotong Wei ◽  
Lin Li ◽  
Ming Gao ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Body Weight ◽  
Linear Regression ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Multiple Linear Regression ◽  
Normal Weight ◽  
Effect Estimate ◽  
Obese Women ◽  
Z Scores

Abstract Background: The association between gestational diabetes mellitus (GDM) and childhood body weight remains controversial, and additional study is needed, especially in Asian populations.Methods: This prospective study investigated the association between maternal glucose concentration, and GDM status and infant body weight from birth to 12 months of age. Linear mixed effects (LME) models and multiple linear regression were used to assess the longitudinal association of GDM with infant growth measured by weight-for-length z-scores (WFLZ), weight-for-age z-scores (WFAZ), and length-for-age z-scores (LFAZ) at birth, 1, 3, 6, 8, and 12 months of age.Results: Offspring born to mothers with GDM had higher WFLZ [β: 0.26 SD units (95% CI: 0.13–0.40)] across infancy than those of mothers without GDM. When stratified analysis by maternal pre-pregnancy body mass index (BMI) status, the association was pronounced in normal-weight [β:0.28 SD units (95% CI: 0.11–0.45)] and overweight/obese women [β: 0.34 SD units (95% CI: 0.09–0.58)] but not in underweight women (P for interaction <0.05). Multiple linear regression found that the effect estimate of GDM on infant WFLZ was highest at birth [β: 0.36 SD units (95% CI: 0.11– 0.61)], remained significant at 1 [β: 0.22 SD units (95% CI: 0.03–0.41)] and 3 [β:0.19 SD units (95% CI: 0.01–0.37)] months of age and decreased across infancy. Maternal GDM status was not associated with infant WFAZ or LFAZ.Conclusions: Maternal GDM status was associated with infant WFLZ, but not WFAZ or LFAZ. The association between GDM status and offspring WFLZ was more pronounced in early infancy or in normal-weight and overweight/obese women. Increased public health efforts to prevent GDM in normal-weight and overweight/obese pre-pregnancy mothers are recommended to control offspring overweight or obesity.

scholarly journals Association of gestational diabetes mellitus with offspring weight status across infancy: a prospective birth cohort study in China

2020 ◽  
Author(s):  
Jiajin Hu ◽  
Yilin Liu ◽  
Xiaotong Wei ◽  
Lin Li ◽  
Ming Gao ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Body Weight ◽  
Linear Regression ◽  
Gestational Diabetes ◽  
Gestational Diabetes Mellitus ◽  
Multiple Linear Regression ◽  
Weight Status ◽  
Normal Weight ◽  
Obese Women ◽  
Childhood Weight

Abstract Background: The association between gestational diabetes mellitus (GDM) and childhood body weight remains controversial, and additional study is needed, especially in Asian populations.Methods: This prospective study investigated the association between maternal glucose concentration, and GDM status and infant body weight from birth to 12 months of age. Linear mixed effects (LME) models and multiple linear regression were used to assess the longitudinal association of GDM with infant growth measured by weight-for-length (WFLZ), weight-for-age (WFAZ), and length-for-age (LFAZ) z-scores at birth, 1, 3, 6, 8, and 12 months of age.Results: Offspring born to mothers with GDM had higher WFLZ [β: 0.26 SD units (95% CI: 0.13–0.40)] across infancy than those of mothers without GDM. The association was more pronounced in normal-weight and overweight/obese women (P for interaction< 0.05). Multiple linear regression found that the effect estimate of GDM on infant WFLZ was highest at birth [β: 0.32 SD units (95% CI: 0.07– 0.57)], remained significant at 1 [β: 0.24 SD units (95% CI: 0.05–0.43)] and 3 [β:0.20 SD units (95% CI: 0.01–0.39)] months of age and decreased across infancy. Maternal GDM status was not associated with infant WFAZ or LFAZ.Conclusions: Maternal GDM status was associated with infant WFLZ, but not WFAZ or LFAZ. The association of GDM status with offspring WFLZ was more pronounced in early infancy or in normal-weight and overweight/obese women. The results may help to identify the critical period and specific GDM-risk groups for childhood weight status.

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