Nonmetric multidimensional scaling: A monte carlo study of the basic parameters

Psychometrika ◽  
1972 ◽  
Vol 37 (3) ◽  
pp. 323-355 ◽  
Author(s):  
Charles R. Sherman
Keyword(s):  
Monte Carlo ◽  
Multidimensional Scaling ◽  
Monte Carlo Study ◽  
Nonmetric Multidimensional Scaling ◽  
Basic Parameters

scholarly journals Monte Carlo study of medium-energy electron penetration in aluminium and silver

Nukleonika ◽  
2015 ◽  
Vol 60 (2) ◽  
pp. 361-366 ◽  
Author(s):  
Asuman Aydın ◽  
Ali Peker
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Monte Carlo Study ◽  
Simulation Method ◽  
Single Scattering ◽  
Medium Energy ◽  
Scattering Model ◽  
Basic Parameters ◽  
Transmission Measurements ◽  
Basic Equations

Abstract Monte Carlo simulations are very useful for many physical processes. The transport of particles was simulated by Monte Carlo calculating the basic parameters such as probabilities of transmitted–reflected and angular-energy distributions after interaction with matter. Monte Carlo simulations of electron scattering based on the single scattering model were presented in the medium-energy region for aluminium and silver matters. Two basic equations are required the elastic scattering cross section and the energy loss. The Rutherford equation for the different screening parameters is investigated. This scattering model is accurate in the energy range from a few keV up to about 0.50 MeV. The reliability of the simulation method is analysed by comparing experimental data from transmission measurements.

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

Monte Carlo study of 50 nm-long single and dual-gate MODFETs: suppression of short-channel effects

1993 ◽  
Vol 3 (9) ◽  
pp. 1719-1728
Author(s):  
P. Dollfus ◽  
P. Hesto ◽  
S. Galdin ◽  
C. Brisset
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Short Channel Effects ◽  
Short Channel ◽  
Channel Effects ◽  
Dual Gate
Sign in / Sign up

Export Citation Format

Share Document