Conformational analysis of double‐tethered chain molecules at an impenetrable interface: A Monte Carlo study

1994 ◽  
Vol 101 (6) ◽  
pp. 5179-5185 ◽  
Author(s):  
Ronald L. Jones ◽  
Richard J. Spontak
Keyword(s):  
Monte Carlo ◽  
Conformational Analysis ◽  
Monte Carlo Study ◽  
Chain Molecules ◽  
Tethered Chain

Self-assembling of chain molecules in low dimensions: A Monte Carlo study

1995 ◽  
Vol 4 (6) ◽  
pp. 1015-1037 ◽  
Author(s):  
Heiko Stettin ◽  
Mirco Wahab ◽  
Peter Schiller ◽  
Hans-Jörg Mögel
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Chain Molecules ◽  
Low Dimensions ◽  
Self Assembling

Effect of surface active sites on adsorption of associating chain molecules in pores: A Monte Carlo study

Adsorption ◽  
1996 ◽  
Vol 2 (1) ◽  
pp. 59-68 ◽  
Author(s):  
Lourdes F. Vega ◽  
Erich A. M�ller ◽  
Luis F. Rull ◽  
Keith E. Gubbins
Keyword(s):  
Monte Carlo ◽  
Active Sites ◽  
Monte Carlo Study ◽  
Chain Molecules ◽  
Surface Active ◽  
Effect Of Surface

Tethered Chains in Concave Volumes. A Monte Carlo Study

1994 ◽  
Vol 59 (10) ◽  
pp. 2166-2189 ◽  
Author(s):  
Karel Procházka ◽  
Zuzana Limpouchová
Keyword(s):  
Monte Carlo ◽  
Spherical Cavity ◽  
Monte Carlo Study ◽  
Volume Effect ◽  
Distribution Functions ◽  
Spherical Cavities ◽  
Chain Conformations ◽  
Tethered Chains ◽  
Self Avoiding Walk ◽  
Tethered Chain

Monte Carlo study of tethered chain conformations in spherical cavities was performed in a relatively broad range of average segment densities (i.e. numbers of tethered chains with increasing length in the sphere). Simulations were performed on a tetrahedral lattice using (i) an equilibrated self-avoiding walk for systems containing a single tethered chain with increasing length, and (ii) a simultaneous self-avoiding walk of many tethered chains in the spherical cavity together with equilibration of the system which was performed by a modified algorithm similar to that of Siepmann and Frenkel. Only a geometric excluded volume effect of segments was considered (i.e. the prohibition principle of a double occupancy of one lattice site by two different segments). Various distribution functions (e.g. distribution of the end-to-end and the end-to-gravity center distances and their orientations with respect either to the radial direction, or to the direction of the first-to-second segment connection, etc.) were calculated and the effect of increasing average segment density in the sphere on conformational characteristics of individual chains was studied. It was found that conformational and orientational properties of relatively short tethered chains are only little affected by increasing segment density (i.e. by the number of chains in the spherical cavity), whereas arrangements of long tethered chains are significantly influenced by the density of the system.

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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