SU-GG-T-325: Improved Organ Sparing by Electronic Brachytherapy: A Monte Carlo Study

2008 ◽  
Vol 35 (6Part14) ◽  
pp. 2800-2800
Author(s):  
J Dingley ◽  
V Taranenko
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Electronic Brachytherapy ◽  
Organ Sparing

Dosimetric optimization of a truncated conical-shaped transmission target for electronic brachytherapy X-ray source: A Monte Carlo study

2017 ◽  
Vol 71 (3) ◽  
pp. 178-184
Author(s):  
Woo Sang Ahn ◽  
Wonsik Choi ◽  
Byungchul Cho ◽  
Jungwon Kwak ◽  
Seung Do Ahn ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
X Ray ◽  
Electronic Brachytherapy

scholarly journals EP-1749 Relation between depth dose and HVL for electronic brachytherapy systems: a Monte Carlo study

2019 ◽  
Vol 133 ◽  
pp. S943-S944
Author(s):  
C. Valdés ◽  
F. Ballester ◽  
J. Vijande ◽  
J. Perez-Calatayud
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Depth Dose ◽  
Electronic Brachytherapy

Depth-dose measurement corrections for the surface electronic brachytherapy beams of an Esteya® unit: a Monte Carlo study

2020 ◽  
Vol 65 (24) ◽  
pp. 245026
Author(s):  
Christian Valdes-Cortez ◽  
Facundo Ballester ◽  
Javier Vijande ◽  
Vicent Gimenez ◽  
Vicent Gimenez-Alventosa ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Study ◽  
Dose Measurement ◽  
Depth Dose ◽  
Electronic Brachytherapy

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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