Relaxation and Creep Quasilinear Viscoelastic Models for Normal Articular Cartilage

1984 ◽  
Vol 106 (2) ◽  
pp. 159-164 ◽  
Author(s):  
B. R. Simon ◽  
R. S. Coats ◽  
S. L.-Y. Woo
Keyword(s):  
Articular Cartilage ◽  
Soft Tissues ◽  
Least Squares Method ◽  
Viscoelastic Model ◽  
Generalized Least Squares ◽  
Constitutive Law ◽  
Analytical Models ◽  
Creep Data ◽  
Bovine Articular Cartilage ◽  
Generalized Least Squares Method

A quasilinear viscoelastic model was used to develop relaxation and creep forms for a constitutive law for soft tissues. Combined relaxation and cyclic test data as well as preconditioned and nonpreconditioned creep data were used to demonstrate the approach for normal bovine articular cartilage. Values for mechanical parameters in the analytical models were determined using a generalized least squares method.

Constructing a summary index using the standardized inverse-covariance weighted average of indicators

2020 ◽  
Vol 20 (4) ◽  
pp. 952-964
Author(s):  
Benjamin Schwab ◽  
Sarah Janzen ◽  
Nicholas P. Magnan ◽  
William M. Thompson
Keyword(s):  
Least Squares Method ◽  
Weighted Average ◽  
Generalized Least Squares ◽  
American Statistical Association ◽  
Cash Transfer ◽  
Transfer Program ◽  
Statistical Association ◽  
Generalized Least Squares Method ◽  
Summary Index ◽  
The Relationship

Researchers often want to examine the relationship between a variable of interest and multiple related outcomes. To avoid problems of inference that arise from testing multiple hypotheses, one can create a summary index of the outcomes. Summary indices facilitate generalizing findings and can be more powerful than individual tests. In this article, we introduce a command, swindex, that implements the generalized least-squares method of index construction proposed by Anderson (2008, Journal of the American Statistical Association 103: 1481–1495). We describe the command and its options and provide an example based on Blattman, Fiala, and Martinez’s (2014, Quarterly Journal of Economics 129: 697–752) evaluation of a cash transfer program in Uganda.

Conformity or differentiation? A U-shaped relationship between peers’ CSR and focal firms’ CSR

2021 ◽  
Vol 15 (2) ◽  
pp. 305-327
Author(s):  
Xianyi Long ◽  
Ting Zhang
Keyword(s):  
Design Methodology ◽  
Least Squares Method ◽  
Environmental Uncertainty ◽  
Generalized Least Squares ◽  
Content Type ◽  
Differentiation Strategy ◽  
Generalized Least Squares Method ◽  
Academic Researchers ◽  
Corporate Social ◽  
Practical Implications

Purpose The purpose of this paper is to investigate the influence of peers’ corporate social responsibility (CSR) on focal firms’ CSR from an integrated perspective. The current study aims to explore whether as peers’ CSR increases focal firms’ CSR would first decrease and then increase. Design/methodology/approach This study is based on a sample consisting of Chinese listed manufacturing firms from 2010 to 2016. Hypotheses are tested by generalized least squares method to minimum heterogeneity and autocorrelation concern. Findings The results show that focal firms’ CSR would first decrease and then increase with the increase in peers’ CSR. Furthermore, this paper found that corporate visibility would stress more value on CSR differentiation strategy and environmental uncertainty would stress more value on CSR conformity strategy, such that the U-shaped relationship would be more pronounced in high corporate visibility or low environmental uncertainty situation. Practical implications The findings may be of interest to the academic researchers and managers. For researchers, it is important to understand how focal firms would practice CSR in response to peers’ CSR, especially through an integrated perspective. For managers, the results show that the best way to invest in CSR activities in response to peers’ CSR follows a U-shaped curve, and corporate visibility and environmental uncertainty are important factors to be considered to make CSR decisions. Originality/value This study contributes to the literature by proposing and examining a U-shaped relationship between peers’ CSR and focal firms’ CSR, which stresses the conformity and differentiation value of CSR simultaneously. Besides, to fully map the effects of peers’ CSR and focal firms’ CSR, this paper considers the moderating roles of internal and external contingencies on this non-linear relationship between the peers’ CSR and focal firms’ CSR.

The least-squares intersection of a family of lines and its application to phase equilibria

1982 ◽  
Vol 60 (15) ◽  
pp. 1978-1981 ◽  
Author(s):  
John W. Lorimer
Keyword(s):  
Phase Equilibria ◽  
Least Squares ◽  
Least Squares Method ◽  
Solid Phase ◽  
Generalized Least Squares ◽  
First Approximation ◽  
Generalized Least Squares Method ◽  
Point Of Intersection ◽  
Straight Lines ◽  
General Method

A generalized least-squares method is described for finding the point of intersection of a family of straight lines, each of which is defined by two experimental points. It is shown that the method of the least-squares triangle (Can. J. Chem. 59, 3076 (1981)) is a good first approximation to the general method. An example demonstrates the method of iteration of both parameters and observations for a problem involving evaluation of solid phase compositions from solubility measurements.

scholarly journals A new method to estimate genetic gain in annual crops

1998 ◽  
Vol 21 (4) ◽  
pp. 551-555 ◽  
Author(s):  
Flávio Breseghello ◽  
Orlando Peixoto de Morais ◽  
Paulo Hideo Nakano Rangel
Keyword(s):  
Genetic Gain ◽  
Least Squares Method ◽  
Generalized Least Squares ◽  
Joint Analysis ◽  
Weighted Estimate ◽  
Arithmetic Means ◽  
Breeding Programs ◽  
Generalized Least Squares Method ◽  
In Series ◽  
Using Data

The genetic gain obtained by breeding programs to improve quantitative traits may be estimated by using data from regional trials. A new statistical method for this estimate is proposed and includes four steps: a) joint analysis of regional trial data using a generalized linear model to obtain adjusted genotype means and covariance matrix of these means for the whole studied period; b) calculation of the arithmetic mean of the adjusted genotype means, exclusively for the group of genotypes evaluated each year; c) direct year comparison of the arithmetic means calculated, and d) estimation of mean genetic gain by regression. Using the generalized least squares method, a weighted estimate of mean genetic gain during the period is calculated. This method permits a better cancellation of genotype x year and genotype x trial/year interactions, thus resulting in more precise estimates. This method can be applied to unbalanced data, allowing the estimation of genetic gain in series of multilocational trials.

scholarly journals Does Institutional Ownership and Bank Monitoring Affect Agency Conflicts? Evidence from an Emerging Market

2020 ◽  
Vol 35 (3) ◽  
pp. 171
Author(s):  
Bagus Dwi Ariyono ◽  
Bowo Setiyono
Keyword(s):  
Least Squares Method ◽  
Emerging Market ◽  
Institutional Ownership ◽  
Generalized Least Squares ◽  
Agency Conflicts ◽  
Bank Monitoring ◽  
Developed Markets ◽  
Irresponsible Behavior ◽  
Generalized Least Squares Method

Introduction/Main Objectives: This study examines the effect of institutional ownership, proxied by government and private ownership, and bank monitoring on agency conflicts. Background Problems: The previous literature focused on agency conflicts, particularly those between managers and shareholders in developed markets, with much less evidence being presented from emerging ones. Novelty: We consider the role of creditors (the banks) in mitigating agency conflicts, and the managers’ irresponsible behavior, which in previous studies has been largely under-elaborated. Research Methods: Using 1,525 observations of 305 non-financial companies that were listed in the 2011-2015 period, we employ the generalized least squares method to deal with potential econometric concern such as autocorrelation and heteroscedasticity. Finding/Results: We find that institutional ownership and bank monitoring, proxied by the number of banks and the share of their loans, are negatively related to agency conflicts. Conclusion: Banks and institutional ownership lead to lower agency conflicts. However, one should mitigate free-rider problems emanated from these relationships.

Removal of Sulfated Glycosaminoglycans Has a Differential Effect on Permeability of Bovine Articular Cartilage as Measured by Direct Permeation and Stress Relaxation

2009 ◽  
Author(s):  
Heath B. Henninger ◽  
Clayton J. Underwood ◽  
Gerard A. Ateshian ◽  
Jeffrey A. Weiss
Keyword(s):  
Articular Cartilage ◽  
Stress Relaxation ◽  
Soft Tissues ◽  
Water Movement ◽  
Experimental Treatment ◽  
Test Methods ◽  
Confined Compression ◽  
Interstitial Fluid Flow ◽  
Bovine Articular Cartilage ◽  
The Impact

Permeability is defined as the ability of a fluid to pass through a porous medium. The ease of water movement is a determinant of the interstitial fluid flow-dependent viscoelastic properties of hydrated soft tissues and also modulates transport of solutes. For articular cartilage, permeability has been quantified directly via permeation experiments and indirectly by analyzing the data from stress relaxation testing under confined compression. It is unclear whether these different methods result in consistent measurements. This further complicates quantification of the effect of an experimental treatment on permeability such as the removal of sulfated glycosaminoglycans (GAGs) [1, 2]. The objective of this study was to elucidate the impact of sulfated GAGs on the permeability of articular cartilage using direct permeation versus stress relaxation testing, and to assess any differences in permeability calculated from the two test methods.

Generalized Least Squares Method, Heteroskedasticity, and Multivariate Regression

2012 ◽  
pp. 179-212
Author(s):  
Jean-Pierre Florens ◽  
Velayoudom Marimoutou ◽  
Anne Peguin-Feissolle ◽  
Josef Perktold ◽  
Marine Carrasco
Keyword(s):  
Least Squares ◽  
Multivariate Regression ◽  
Least Squares Method ◽  
Generalized Least Squares ◽  
Generalized Least Squares Method
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