Influence of Specific Site Binding on the Interactions between Charged Colloids:  A (N,V,T) Monte Carlo Study

2000 ◽  
Vol 104 (45) ◽  
pp. 10588-10596 ◽  
Author(s):  
A. Delville
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Specific Site ◽  
Charged Colloids ◽  
Site Binding

Monte Carlo study of structural ordering in charged colloids using a long-range attractive interaction

1998 ◽  
Vol 58 (2) ◽  
pp. 2237-2246 ◽  
Author(s):  
B. V. R. Tata ◽  
Norio Ise
Keyword(s):  
Monte Carlo ◽  
Long Range ◽  
Monte Carlo Study ◽  
Attractive Interaction ◽  
Structural Ordering ◽  
Charged Colloids

Electrostatic Attraction and/or Repulsion Between Charged Colloids: A (NVT) Monte-Carlo Study

2000 ◽  
Vol 24 (1-3) ◽  
pp. 1-24 ◽  
Author(s):  
A. Delville ◽  
R. J.-M. Pellenq
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Electrostatic Attraction ◽  
Charged Colloids

An integral equation and Monte Carlo study of homo- and hetero nuclear square-well diatomic fluids

2000 ◽  
Vol 98 (24) ◽  
pp. 2033-2043
Author(s):  
Vít Jirásek, Stanislav Labík, Anatol Ma
Keyword(s):  
Integral Equation ◽  
Monte Carlo ◽  
Monte Carlo Study ◽  
Square Well

Analyzing Observed Composite Differences Across Groups

Methodology ◽  
2013 ◽  
Vol 9 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Holger Steinmetz
Keyword(s):  
Monte Carlo ◽  
Structural Equation Modeling ◽  
Measurement Invariance ◽  
Structural Equation ◽  
Monte Carlo Study ◽  
Equation Modeling ◽  
Factor Loadings ◽  
Latent Mean Differences ◽  
Partial Invariance ◽  
Mean Differences

Although the use of structural equation modeling has increased during the last decades, the typical procedure to investigate mean differences across groups is still to create an observed composite score from several indicators and to compare the composite’s mean across the groups. Whereas the structural equation modeling literature has emphasized that a comparison of latent means presupposes equal factor loadings and indicator intercepts for most of the indicators (i.e., partial invariance), it is still unknown if partial invariance is sufficient when relying on observed composites. This Monte-Carlo study investigated whether one or two unequal factor loadings and indicator intercepts in a composite can lead to wrong conclusions regarding latent mean differences. Results show that unequal indicator intercepts substantially affect the composite mean difference and the probability of a significant composite difference. In contrast, unequal factor loadings demonstrate only small effects. It is concluded that analyses of composite differences are only warranted in conditions of full measurement invariance, and the author recommends the analyses of latent mean differences with structural equation modeling instead.

Detecting Between-Groups Heteroscedasticity in MMR: A Monte Carlo Study

2011 ◽  
Author(s):  
Patrick J. Rosopa ◽  
Amber N. Schroeder ◽  
Jessica Doll
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study
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